bluuebunny/crossref_metadata_2025 huggingface dataset:
Profile of Phenolic Compounds and Antioxidant Activity of Celery (Apium graveolens) Juices Obtained from Pulp after α-Amylase Treatment from Aspergillus oryzae
Authors: Szarek Natalia , Jaworska Grażyna , Hanus Paweł
Published: March 2024

The purpose of this study was to determine the content of certain phenolic compounds, antioxidant activity, pressing efficiency, extract content, and sugars in celeriac juices obtained from the pulp after α-amylase treatment from Aspergillus oryzae. The test material consisted of peeled and unpeeled celery pulp kept at a temperature of 25 °C with and without the enzyme for a period of 30 and 60 min. The juices obtained from them were analyzed for the content of selected phenolic acids and flavonoids using the UPLC-PDA-ESI-MS/MS method, for antioxidant activity measured using the ABTS˙+ and DPPH˙ method, and for the total polyphenol content using the F-C method. Additionally, the juice pressing efficiency, the extract content using the refractometer method, and the sugar content using the HPLC method were checked. Significantly higher antioxidant activity, pressing yield, and average content of caffeic acid glucoside, quinic acid, kaempferol-3,7-di-O-glucoside, and chrysoeriol-7-O-apiosylglucoside were obtained in juices from peeled celery. Maceration of the pulp with amylase resulted in a significant reduction in antioxidant activity compared to control samples. An is-total increase of 17–41% in total flavonoid content was observed in all juices tested after treatment with the enzyme for 30 and 60 min, and the phenolic acid content increased by 4–41% after treatment of the pulp with amylase for 60 min. The 60 min holding of the pulp at 25 °C, including with the enzyme, was shown to decrease the antioxidant activity and the content of quinic acid, ferulic acid, and chrysoriol-7-O-apiose-glucoside in the juices tested compared to the samples held for 30 min, while the content of other phenolic acids and flavonoids increased. In addition, after 60 min of enzymatic maceration, the pressing yield of the juices increased.
Mycotransformation of Commercial Grade Cypermethrin Dispersion by Aspergillus terreus PDB-B Strain Isolated from Lake Sediments of Kulamangalam, Madurai
Authors: Kannan Priyadharshini , Baskaran Hidayah , Juliana Selvaraj Jemima Balaselvi , Saeid Agnieszka , Kiruba Nester Jennifer Michellin
Published: March 2024

A fungal isolate Aspergillus terreus PDB-B (accession number: MT774567.1), which could tolerate up to 500 mg/L of cypermethrin, was isolated from the lake sediments of Kulamangalam tropical lake, Madurai, and identified by internal transcribed spacer (ITS) sequencing followed by phylogenetic analysis. The biotransformation potential of the strain was compared with five other strains (A, J, UN2, M1 and SM108) as a consortium, which were tentatively identified as Aspergillus glaucus, Aspergillus niger, Aspergillus flavus, Aspergillus terreus, and Aspergillus flavus, respectively. Batch culture and soil microcosm studies were conducted to explore biotransformation using plate-based enzymatic screening and GC-MS. A mycotransformation pathway was predicted based on a comparative analysis of the transformation products (TPs) obtained. The cytotoxicity assay revealed that the presence of (3-methylphenyl) methanol and isopropyl ether could be relevant to the high rate of lethality.
Electrochemical Monitoring in Anticoagulation Therapy
Authors: Mruthunjaya Ashwin K. V. , Torriero Angel A. J.
Published: March 2024

The process of blood coagulation, wherein circulating blood transforms into a clot in response to an internal or external injury, is a critical physiological mechanism. Monitoring this coagulation process is vital to ensure that blood clotting neither occurs too rapidly nor too slowly. Anticoagulants, a category of medications designed to prevent and treat blood clots, require meticulous monitoring to optimise dosage, enhance clinical outcomes, and minimise adverse effects. This review article delves into the various stages of blood coagulation, explores commonly used anticoagulants and their targets within the coagulation enzyme system, and emphasises the electrochemical methods employed in anticoagulant testing. Electrochemical sensors for anticoagulant monitoring are categorised into two types. The first type focuses on assays measuring thrombin activity via electrochemical techniques. The second type involves modified electrode surfaces that either directly measure the redox behaviours of anticoagulants or monitor the responses of standard redox probes in the presence of these drugs. This review comprehensively lists different electrode compositions and their detection and quantification limits. Additionally, it discusses the potential of employing a universal calibration plot to replace individual drug-specific calibrations. The presented insights are anticipated to significantly contribute to the sensor community’s efforts in this field.
Realization of 4 × 200 Gbps 4-QAM OFDM-OWC System Using Higher Order OAM Modes for HAP-to-Satellites Scenario
Authors: Kumari Meet , Mishra Satyendra K.
Published: March 2024

Recently, there has been an increase in interest in using optical wireless communication (OWC) links on high-altitude platforms (HAPs) for satellite applications. We implement an orbital angular momentum (OAM) multiplexed orthogonal frequency division multiplexing (OFDM) system using an OWC link. A space-to-air scenario is considered in which transmission pointing errors, geometric loss, turbulence, and additional link losses are taken into account to extend the transmission range, system capacity, and throughput. At 200 Gbps per channel data rate, four different OAM modes are implemented with higher order Laguerre–Gaussian (LG) modes of [0,0], [0,13], [0,40], and [0,80]. An aggregate 800 Gbps data rate can deliver a maximum OWC range of 3300–5000 km for all channels. The maximum received power over the 1000 km range is −19.34 to −32.59 dBm with an additional gain of 0–2.5 dB. It is also possible to obtain a better performance over large distances of 500–3500 km with an error vector magnitude of 2.98–17.5%. Furthermore, a high gain of −40.80 dB, a signal-to-noise ratio (SNR) of 55.21 dB, and an optical SNR of 67.25 dB can be achieved for varied transmitter pointing errors of 0.1 rad. As compared to other literature, this system exhibits a superior performance.
Research on the Frequency Stabilization System of an External Cavity Diode Laser Based on Rubidium Atomic Modulation Transfer Spectroscopy Technology
Authors: Wu Yueyang , Qin Fangjun , Ding Zhichao , Xu Rui , Li Dongyi
Published: March 2024

To achieve high-frequency stability on the external cavity diode laser (ECDL), a 780 nm ECDL serves as the seed light source, and its frequency is precisely locked to the saturated absorption peak of rubidium (Rb) atoms using modulation transfer spectroscopy (MTS) technology. For improving the performance of frequency locking, the scheme is designed to find the optimal operating conditions. Correlations between the frequency discrimination signal (FDS) and critical parameters, such as the temperature of the Rb cell, the power ratio of the probe and pump light, and the frequency and amplitude of the modulation and demodulation signals, are observed to attain the optimal conditions for frequency locking. To evaluate the performance of the frequency-stabilized 780 nm ECDL, a dual-beam heterodyne setup was constructed. Through this arrangement, the laser linewidth, approximately 65.4 kHz, is measured. Then, the frequency stability of the laser, quantified as low as 4.886 × 10−12 @32 s, is determined by measuring the beat-frequency signal with a frequency counter and calculating the Allan variance. Furthermore, using the realized frequency locking technology, the 780 nm ECDL can achieve long-term stabilization even after 25 h. The test results show the exceptional performance of the implemented frequency stabilization system for the 780 nm ECDL.
Coupled Oxygen-Enriched Combustion in Cement Industry CO2 Capture System: Process Modeling and Exergy Analysis
Authors: Wang Leichao , Shi Bin
Published: March 2024

The cement industry is regarded as one of the primary producers of world carbon emissions; hence, lowering its carbon emissions is vital for fostering the development of a low-carbon economy. Carbon capture, utilization, and storage (CCUS) technologies play significant roles in sectors dominated by fossil energy. This study aimed to address issues such as high exhaust gas volume, low CO2 concentration, high pollutant content, and difficulty in carbon capture during cement production by combining traditional cement production processes with cryogenic air separation technology and CO2 purification and compression technology. Aspen Plus® was used to create the production model in its entirety, and a sensitivity analysis was conducted on pertinent production parameters. The findings demonstrate that linking the oxygen-enriched combustion process with the cement manufacturing process may decrease the exhaust gas flow by 54.62%, raise the CO2 mass fraction to 94.83%, cut coal usage by 30%, and considerably enhance energy utilization efficiency. An exergy analysis showed that the exergy efficiency of the complete kiln system was risen by 17.56% compared to typical manufacturing procedures. However, the cryogenic air separation system had a relatively low exergy efficiency in the subsidiary subsystems, while the clinker cooling system and flue gas circulation system suffered significant exergy efficiency losses. The rotary kiln system, which is the main source of the exergy losses, also had low exergy efficiency in the traditional production process.
Effect of Acid-Injection Mode on Conductivity for Acid-Fracturing Stimulation in Ultra-Deep Tight Carbonate Reservoirs
Authors: Liu Jiangyu , Ren Dengfeng , Feng Shaobo , Liu Ju , Qin Shiyong , Qiao Xin , Gou Bo
Published: March 2024

The conductivity of acid-etched fractures and the subsequent production response are influenced by the injection mode of the fracturing fluid and acid fluid during acid fracturing in a carbonate reservoir. However, there has been a lack of comprehensive and systematic experimental research on the impact of commonly used injection modes in oilfields on conductivity, which directly affects the optimal selection of acid-fracturing injection modes. To address this gap, the present study focuses on underground rock samples, acid systems, and fracturing fluid obtained from ultra-deep carbonate reservoirs in the Fuman Oilfield. Experimental investigations were conducted to examine the conductivity of hydraulic fractures etched by various types of acid fluids under five different injection modes: fracturing fluid + self-generating acid or cross-linked acid; fracturing fluid + self-generating acid + cross-linked acid. The findings demonstrate that the implementation of multi-stage alternating acid injection results in the formation of communication channels, vugular pore space, and natural micro-cracks, as well as grooves and fish-scales due to enhanced etching effects. The elevation change, amount of dissolved rock, and conductivity exhibited by rock plates are significantly higher in comparison to those achieved through the single-acid injection mode while maintaining superior conductivity. It is recommended for optimal conductivity and retention rate in the Fuman Oilfield to adopt two stages of alternating acid-fracturing injection mode. Field application demonstrated that two-stages of alternating acid-fracturing generate more pronounced production response than the adjacent wells.
Algorithm for Correlation Diagnosis in Multivariate Process Quality Based on the Optimal Typical Correlated Component Pair Group
Authors: Niu Qing , Cheng Shujie , Qiu Zeyang
Published: March 2024

Correlation diagnosis in multivariate process quality management is an important and challenging issue. In this paper, a new approach based on the optimal typical correlated component pair group (OTCCPG) is proposed. Firstly, the theorem of correlation decomposition is proved to decompose the correlation of all the quality components as serial correlations of component pairs, and then according to the transitivity of correlations of component pairs, the decomposition result is represented by a correlation set of typical correlated component pairs. Finally, an algorithm for OTCCPG based on the maximum correlation spanning tree (MCST) is proposed, and T2 control charts to monitor the correlations of component pairs in OTCCPG are established to form the correlation diagnostic system. Theoretical analysis and practice prove that the proposed method could reduce the space complexity of the diagnostic system greatly.
Mitigation of Renewable Energy Source Production Variability in Residential Stock through Small-Scale Gas–Liquid Energy Storage Technology Application
Authors: Vallati Andrea , Di Matteo Miriam , Pompei Laura , Nardecchia Fabio , Fiorini Costanza Vittoria
Published: March 2024

Despite renewable energy source integration being a well-established requirement in international policies, energy systems still face some unresolved issues, including the intermittence of production. To tackle this problem, a viable solution could comprise the off-peak storage of electricity production excess, to be consumed later during peak-load hours. The transition from the diffuse pattern of centralized generation to the distributed model, involving energy communities, suggests an additional aspect to manage: the spatial constraints of systems for domestic applications. Compressed-air energy storage represents a promising Power-to-Power technology for small-scale energy integration. This study proposes the application of a gas–liquid energy storage system (GLES) in a residential building, using renewable energy excess from a photovoltaic (PV) array. The performance of the proposed system, whose operation involves the compression of the gaseous mass through a piston operated by mineral oil, was evaluated through energy analysis performed simulating the devices and their coupling with the load profiles of the building. The thermodynamic model of storage was validated using data from an experimental campaign on a prototype. A sensitivity study, acting on the features of the system, such as the compression rate and vessel size, allowed us to compare the absorbed PV energy excess, the coverage of the building energy demand during the expansion phase, and the electrical efficiency of a daily cycle. The results obtained, together with the related economic analysis, were used to quantify the market potential of the proposed solution, to be exploited as a mechanical alternative to conventional electric batteries in dwellings.
Amount Estimation Method for Food Intake Based on Color and Depth Images through Deep Learning
Authors: Lee Dong-seok , Kwon Soon-kak
Published: March 2024

In this paper, we propose an amount estimation method for food intake based on both color and depth images. Two pairs of color and depth images are captured pre- and post-meals. The pre- and post-meal color images are employed to detect food types and food existence regions using Mask R-CNN. The post-meal color image is spatially transformed to match the food region locations between the pre- and post-meal color images. The same transformation is also performed on the post-meal depth image. The pixel values of the post-meal depth image are compensated to reflect 3D position changes caused by the image transformation. In both the pre- and post-meal depth images, a space volume for each food region is calculated by dividing the space between the food surfaces and the camera into multiple tetrahedra. The food intake amounts are estimated as the difference in space volumes calculated from the pre- and post-meal depth images. From the simulation results, we verify that the proposed method estimates the food intake amount with an error of up to 2.2%.
Pulse Accumulation Approach Based on Signal Phase Estimation for Doppler Wind Lidar
Authors: Liang Naiyuan , Yu Xiaonan , Lin Peng , Chang Shuai , Zhang Huijun , Su Chen , Luo Fengchen , Tong Shoufeng
Published: March 2024

Coherent Doppler wind lidar (CDWL) uses transmitted laser pulses to measure wind velocity distribution. However, the echo signal of CDWL is easily affected by atmospheric turbulence, which can decrease the signal-to-noise ratio (SNR) of lidar. To improve the SNR, this paper proposes a pulse accumulation method based on the cross-correlation function to estimate the phase of the signal. Compared with incoherent pulse accumulation, the proposed method significantly enhances the correlation between signals from different periods to obtain high SNR gains that arise from pulse accumulation. Using simulation, the study evaluates the effectiveness of this phase estimation method and its robustness against noise in algorithms which analyze Doppler frequency shifts. Furthermore, a CDWL is developed for measuring the speed of an indoor motor turntable and the outdoor atmospheric wind field. The phase estimation method yielded SNR gains of 28.18 dB and 32.03 dB for accumulation numbers of 500 and 1500, respectively. The implementation of this method in motor turntable speed measurements demonstrated a significant reduction in speed error—averaging 9.18% lower than that of incoherent accumulation lidar systems. In experiments that measure atmospheric wind fields, the linear fit curve slope between the measured wind speed and the wind speed measured via a commercial wind-measuring lidar can be reduced from 1.146 to 1.093.
Task Offloading Strategy for Unmanned Aerial Vehicle Power Inspection Based on Deep Reinforcement Learning
Authors: Zhuang Wei , Xing Fanan , Lu Yuhang
Published: March 2024

With the ongoing advancement of electric power Internet of Things (IoT), traditional power inspection methods face challenges such as low efficiency and high risk. Unmanned aerial vehicles (UAVs) have emerged as a more efficient solution for inspecting power facilities due to their high maneuverability, excellent line-of-sight communication capabilities, and strong adaptability. However, UAVs typically grapple with limited computational power and energy resources, which constrain their effectiveness in handling computationally intensive and latency-sensitive inspection tasks. In response to this issue, we propose a UAV task offloading strategy based on deep reinforcement learning (DRL), which is designed for power inspection scenarios consisting of mobile edge computing (MEC) servers and multiple UAVs. Firstly, we propose an innovative UAV-Edge server collaborative computing architecture to fully exploit the mobility of UAVs and the high-performance computing capabilities of MEC servers. Secondly, we established a computational model concerning energy consumption and task processing latency in the UAV power inspection system, enhancing our understanding of the trade-offs involved in UAV offloading strategies. Finally, we formalize the task offloading problem as a multi-objective optimization issue and simultaneously model it as a Markov Decision Process (MDP). Subsequently, we proposed a task offloading algorithm based on a Deep Deterministic Policy Gradient (OTDDPG) to obtain the optimal task offloading strategy for UAVs. The simulation results demonstrated that this approach outperforms baseline methods with significant improvements in task processing latency and energy consumption.
Industrial Internet of Things Gateway with OPC UA Based on Sitara AM335X with ModbusE Acquisition Cycle Performance Analysis
Authors: Ventuneac Cornel , Gaitan Vasile Gheorghita
Published: March 2024

This article presents the hardware and software architectures used to implement the Modbus Extension (ModbusE) IIoT gateway, the performance of the acquisition cycle at the PRU real-time programmable core level, the acquisition cycle communication flow—dispatcher—OPC UA server (Linux)—OPC UA client (Windows) as well as the performance analysis of data communications between the IIoT ModbusE gateway and the OPC UA client (Windows). In order to be able to implement both the ModbusE acquisition cycle and the OPC UA server, the BeagleBone Black Board was chosen as the hardware platform. This board uses the Sitara AM335x processor (Texas Instruments (TI), Dallas, TX, USA) from Texas Instruments. Thus, the acquisition cycle was implemented on the PRU0 real-time core, and the OPC UA server, running under the Linux operating system, was implemented on the ARM Cortex A8 processor. From the analysis of the communication speed of the messages between the OPC UA client and the ModbusE servers, it was found that the ModbusE acquisition cycle speed was higher than the acquisition speed of the OPC UA client.
Sensors on Internet of Things Systems for the Sustainable Development of Smart Cities: A Systematic Literature Review
Authors: Zeng Fan , Pang Chuan , Tang Huajun
Published: March 2024

The Internet of Things (IoT) is a critical component of smart cities and a key contributor to the achievement of the United Nations Sustainable Development Goal (UNSDG) 11: Sustainable Cities and Communities. The IoT is an infrastructure that enables devices to communicate with each other over the Internet, providing critical components for smart cities, such as data collection, generation, processing, analysis, and application handling. IoT-based applications can promote sustainable urban development. Many studies demonstrate how the IoT can improve smart cities’ sustainable development. This systematic literature review provides valuable insights into the utilization of the IoT in the context of smart cities, with a particular focus on its implications for sustainable urban development. Based on an analysis of 73 publications, we discuss the role of IoT in the sustainable development of smart cities, focusing on smart communities, smart transportation, disaster management, privacy and security, and emerging applications. In each domain, we have detailed the attributes of IoT sensors. In addition, we have examined various communication technologies and protocols suitable for transmitting sensor-generated data. We have also presented the methods for analyzing and integrating these data within the IoT application layer. Finally, we identify research gaps in the literature, highlighting areas that require further investigation.
MAM-E: Mammographic Synthetic Image Generation with Diffusion Models
Authors: Montoya-del-Angel Ricardo , Sam-Millan Karla , Vilanova Joan C. , Martí Robert
Published: March 2024

Generative models are used as an alternative data augmentation technique to alleviate the data scarcity problem faced in the medical imaging field. Diffusion models have gathered special attention due to their innovative generation approach, the high quality of the generated images, and their relatively less complex training process compared with Generative Adversarial Networks. Still, the implementation of such models in the medical domain remains at an early stage. In this work, we propose exploring the use of diffusion models for the generation of high-quality, full-field digital mammograms using state-of-the-art conditional diffusion pipelines. Additionally, we propose using stable diffusion models for the inpainting of synthetic mass-like lesions on healthy mammograms. We introduce MAM-E, a pipeline of generative models for high-quality mammography synthesis controlled by a text prompt and capable of generating synthetic mass-like lesions on specific regions of the breast. Finally, we provide quantitative and qualitative assessment of the generated images and easy-to-use graphical user interfaces for mammography synthesis.
Blockchain-Based Method for Spatial Retrieval and Verification of Remote Sensing Images
Authors: Liu Yujie , Chang Yuanfei
Published: March 2024

Remote sensing image is a vital basis for land management decisions. The protection of remote sensing images has seen the application of blockchain’s notarization function by many scholars. Yet, research on efficient retrieval of such images on the blockchain remains sparse. Addressing this issue, this paper introduces a blockchain-based spatial index verification method using Hyperledger Fabric. It linearizes the spatial information of remote sensing images via Geohash and integrates it with LSM trees for effective retrieval and verification. The system also incorporates IPFS as an underlying storage unit for Hyperledger Fabric, ensuring the safe storage and transmission of images. The experiments indicate that this method significantly reduces the latency in data retrieval and verification without impacting the write performance of Hyperledger Fabric, enhancing throughput and providing a solid foundation for efficient blockchain-based verification of remote sensing images in land registry systems.
Dynamic Mode Decomposition of Multiphoton and Stimulated Emission Depletion Microscopy Data for Analysis of Fluorescent Probes in Cellular Membranes
Authors: Wüstner Daniel , Egebjerg Jacob Marcus , Lauritsen Line
Published: March 2024

An analysis of the membrane organization and intracellular trafficking of lipids often relies on multiphoton (MP) and super-resolution microscopy of fluorescent lipid probes. A disadvantage of particularly intrinsically fluorescent lipid probes, such as the cholesterol and ergosterol analogue, dehydroergosterol (DHE), is their low MP absorption cross-section, resulting in a low signal-to-noise ratio (SNR) in live-cell imaging. Stimulated emission depletion (STED) microscopy of membrane probes like Nile Red enables one to resolve membrane features beyond the diffraction limit but exposes the sample to a lot of excitation light and suffers from a low SNR and photobleaching. Here, dynamic mode decomposition (DMD) and its variant, higher-order DMD (HoDMD), are applied to efficiently reconstruct and denoise the MP and STED microscopy data of lipid probes, allowing for an improved visualization of the membranes in cells. HoDMD also allows us to decompose and reconstruct two-photon polarimetry images of TopFluor-cholesterol in model and cellular membranes. Finally, DMD is shown to not only reconstruct and denoise 3D-STED image stacks of Nile Red-labeled cells but also to predict unseen image frames, thereby allowing for interpolation images along the optical axis. This important feature of DMD can be used to reduce the number of image acquisitions, thereby minimizing the light exposure of biological samples without compromising image quality. Thus, DMD as a computational tool enables gentler live-cell imaging of fluorescent probes in cellular membranes by MP and STED microscopy.
Integrating Modular Pipelines with End-to-End Learning: A Hybrid Approach for Robust and Reliable Autonomous Driving Systems
Authors: Rosero Luis Alberto , Gomes Iago Pachêco , da Silva Júnior Anderson Rodrigues , Przewodowski Carlos André , Wolf Denis Fernando , Osório Fernando Santos
Published: March 2024

Autonomous driving navigation relies on diverse approaches, each with advantages and limitations depending on various factors. For HD maps, modular systems excel, while end-to-end methods dominate mapless scenarios. However, few leverage the strengths of both. This paper innovates by proposing a hybrid architecture that seamlessly integrates modular perception and control modules with data-driven path planning. This innovative design leverages the strengths of both approaches, enabling a clear understanding and debugging of individual components while simultaneously harnessing the learning power of end-to-end approaches. Our proposed architecture achieved first and second place in the 2023 CARLA Autonomous Driving Challenge’s SENSORS and MAP tracks, respectively. These results demonstrate the architecture’s effectiveness in both map-based and mapless navigation. We achieved a driving score of 41.56 and the highest route completion of 86.03 in the MAP track of the CARLA Challenge leaderboard 1, and driving scores of 35.36 and 1.23 in the CARLA Challenge SENSOR track with route completions of 85.01 and 9.55, for, respectively, leaderboard 1 and 2. The results of leaderboard 2 raised the hybrid architecture to the first position, winning the edition of the 2023 CARLA Autonomous Driving Competition.
On the Applicability of Ground-Based Microwave Radiometers for Urban Boundary Layer Research
Authors: Bartsevich Michael , Rahman Kalimur , Addasi Omar , Ramamurthy Prathap
Published: March 2024

Significant knowledge gaps exist in our understanding of urban boundary layer processes, particularly the hygrothermal state. The earth system community has successfully used microwave radiometers for several decades. However, the applicability in complex urban environments has never been adequately tested. Here, observations from a microwave radiometer are compared to radiosonde readings in a densely urbanized site in Houston, Texas. The site was influenced by both an urban heat island and the sea breeze phenomenon. The analysis showed significant disagreement between the virtual potential temperature predicted by the microwave radiometer and the radiosonde for all periods within the boundary layer. However, the values were reasonably comparable above the boundary layer. The microwave radiometer incorrectly predicted an inversion layer instead of a mixed layer during convective periods. The microwave radiometer measurements deviated from the radiosonde measurements throughout the lower troposphere for the relative humidity.
The Synergistic Relationship between Low-Carbon Development of Road Freight Transport and Its Economic Efficiency—A Case Study of Wuhan, China
Authors: Li Jia , Zheng Yahong , Liu Bing , Chen Yanyi , Zhong Zhihang , Dong Chenyu , Wang Chaoqun
Published: March 2024

Road freight transport, an essential component of the logistics sector, faces challenges: high cost, low efficiency, and environmental impact. The need has become urgent to achieve a synergistic balance between low-carbon and high-efficiency development. This study used a three-stage DEA–Malmquist index model to analyze the road freight efficiency of Wuhan and 16 other cities in China from 2015 to 2020, and we compared Wuhan’s performance with its peers. In addition, grey correlation analysis was used to evaluate the low-carbon development of urban road freight transport in Wuhan. Through the calculation of the degree of synergy between low-carbon development and freight transport efficiency, this study provides insights into the synergistic development of low-carbon and efficient road freight transport in Wuhan. The key findings show that the total factor productivity of road freight transport in Wuhan was generally on a downward trend from 2015 to 2020, and was lower than that of the average of the 17 selected Chinese cities. The carbon emissions of road freight transport in Wuhan inversely related to its scale efficiency. This study also points out that the synergy between low-carbon development and the economic efficiency of road freight transport in Wuhan is not high and needs to be further integrated and optimized.
Ecotoxicological Evaluation of Safener and Antimicrobial Additives in Isoxaflutole-Based Herbicide Formulations
Authors: Takács Eszter , Lázár Diána , Siakwa Augustine , Klátyik Szandra , Mörtl Mária , Kocsányi László , Barócsi Attila , Lenk Sándor , Lengyel Edina , Székács András
Published: March 2024

The environmental load by isoxaflutole and its formulated herbicide products has increasingly become apparent because, after the ban of atrazine, isoxaflutole has become its replacement active ingredient (a.i.). Obtaining information regarding the fate of this a.i. in environmental matrices and its ecotoxicological effects on aquatic organisms is essential for the risk assessment of the herbicide. In this study, the effects of Merlin Flexx- and Merlin WG75 formulated isoxaflutole-based herbicide products and two selected additives (cyprosulfamide safener and 1,2-benzisothiazol-3(2H)-one antimicrobial agent) were investigated on Raphidocelis subcapitata in growth inhibition assays. In ecotoxicological tests, two conventional (optical density and chlorophyll-a content) and two induced fluorescence-based (Fv*/Fp: efficiency of the photosystem PSII and Rfd* changes in the observed ratio of fluorescence decrease) endpoints were determined by UV-spectrophotometer and by our FluoroMeter Module, respectively. Furthermore, dissipation of isoxaflutole alone and in its formulated products was examined by an HPLC-UV method. In ecotoxicological assays, the fluorescence-based Rfd* was observed as the most sensitive endpoint. In this study, the effects of the safener cyprosulfamide and the antimicrobial agent 1,2-benzisothiazol-3(2H)-one on R. subcapitata is firstly reported. The results indicated that the isoxaflutole-equivalent toxicity of the mixture of the isoxaflutole–safener–antimicrobial agent triggered lower toxicity (EC50 = 2.81 ± 0.22 mg/L) compared to the individual effect of the a.i. (EC50 = 0.02 ± 0.00 mg/L). The Merlin Flexx formulation (EC50 = 27.04 ± 1.41 mg/L) was found to be approximately 50-fold less toxic than Merlin WG75, which can be explained by the different chemical characteristics and quantity of additives in them. The additives influenced the dissipation of the a.i. in Z8 medium, as the DT50 value decreased by approximately 1.2- and 3.5-fold under light and dark conditions, respectively.
The Shock Cone Instabilities and Quasi-Periodic Oscillations around the Hartle–Thorne Black Hole
Authors: Donmez Orhan , Dogan Fatih
Published: March 2024

To explain the observed X-ray data in a black hole–accreting matter system and understand the physical mechanisms behind QPOs, we have numerically modeled the dynamical and oscillation properties of the shock cone formed around both slowly and rapidly rotating Hartle–Thorne black holes, resulting from the mechanism of Bondi–Hoyle–Lyttleton (BHL). According to the numerical simulations, an increase in the quadrupole parameter leads to a decrease in the shock cone opening angle around the black hole. A larger quadrupole parameter results in more matter falling into the black hole within the cone. The combination of the quadrupole parameter and black hole rotation causes the matter inside the cone to exhibit chaotic motion. These dynamical changes and chaotic behavior of the shock cones excite the fundamental oscillation modes. Moreover, new frequencies have been formed due to the nonlinear coupling of the fundamental modes. Conversely, we have numerically studied the behavior of cones formed around rapidly rotating Hartle–Thorne black holes and found differences and similarities to those obtained from slowly rotating cases. Finally, comparing the outcomes obtained fromHartle–Thorne gravity with the results fromKerr and Einstein–Gauss–Bonnet (EGB) gravities reveals the impact of the quadrupole parameter on the shock cone and QPOs.
Scientific Highlights of the AGILE Gamma-ray Mission
Authors: Vercellone Stefano , Pittori Carlotta , Tavani Marco
Published: March 2024

The γ-ray sky above a few tens of megaelectronvolts (MeV) reveals some of the most powerful and energetic phenomena of our Universe. The Astrorivelatore Gamma ad Immagini LEggero (AGILE) Gamma-ray Mission was launched in 2007 with the aim of observing celestial sources by means of three instruments covering a wide range of energies, from hard X-rays up to 30 GeV. Thanks to its wide field of view, AGILE set to observe and detect emission from pulsars, pulsar wind nebulae, gamma-ray bursts, active galactic nuclei, fast radio bursts, terrestrial gamma-ray flashes, and the electromagnetic counterparts of neutrinos and gravitational waves. In particular, the fast on-ground processing and analysis chain allowed the AGILE team to promptly respond to transient events, and activate or participate in multiwavelength observing campaigns. Eventually, after 17 years of operations, the AGILE Italian scientific satellite re-entered the atmosphere on 14 February 2024, ending its intense activity as a hunter of some of the most energetic cosmic sources in the Universe that emit X and γ-rays. We will review the most relevant AGILE results to date and their impact on the advancements of theoretical models.
Influence of Maternal Nutrition and One-Carbon Metabolites Supplementation during Early Pregnancy on Bovine Fetal Small Intestine Vascularity and Cell Proliferation
Authors: Daneshi Mojtaba , Borowicz Pawel P. , Entzie Yssi L. , Syring Jessica G. , King Layla E. , Safain Kazi Sarjana , Anas Muhammad , Reynolds Lawrence P. , Ward Alison K. , Dahlen Carl R. , Crouse Matthew S. , Caton Joel S.
Published: March 2024

To investigate the effects of nutrient restriction and one-carbon metabolite (OCM) supplementation (folate, vitamin B12, methionine, and choline) on fetal small intestine weight, vascularity, and cell proliferation, 29 (n = 7 ± 1 per treatment) crossbred Angus beef heifers (436 ± 42 kg) were estrous synchronized and conceived by artificial insemination with female sexed semen from a single sire. Then, they were allotted randomly to one of four treatments in a 2 × 2 factorial arrangement with the main factors of nutritional plane [control (CON) vs. restricted feed intake (RES)] and OCM supplementation [without OCM (−OCM) or with OCM (+OCM)]. Heifers receiving the CON level of intake were fed to target an average daily gain of 0.45 kg/day, which would allow them to reach 80% of mature BW by calving. Heifers receiving the RES level of intake were fed to lose 0.23 kg/heifer daily, which mimics observed production responses in heifers that experience a diet and environment change during early gestation. Targeted heifer gain and OCM treatments were administered from d 0 to 63 of gestation, and then all heifers were fed a common diet targeting 0.45 kg/d gain until d 161 of gestation, when heifers were slaughtered, and fetal jejunum was collected. Gain had no effect (p = 0.17) on the fetal small intestinal weight. However, OCM treatments (p = 0.02) displayed less weight compared to the −OCM groups. Capillary area density was increased in fetal jejunal villi of RES − OCM (p = 0.02). Vascular endothelial growth factor receptor 2 (VEGFR2) positivity ratio tended to be greater (p = 0.08) in villi and was less in the crypts (p = 0.02) of the RES + OCM group. Cell proliferation decreased (p = 0.02) in villi and crypts of fetal jejunal tissue from heifers fed the RES + OCM treatment compared with all groups and CON − OCM, respectively. Spatial cell density increased in RES − OCM compared with CON + OCM (p = 0.05). Combined, these data show OCM supplementation can increase expression of VEGFR2 in jejunal villi, which will promote maintenance of the microvascular beds, while at the same time decreasing small intestine weight and crypt cell proliferation.
Should I Take Aspirin? (SITA): randomised controlled trial of a decision aid for cancer chemoprevention
Authors: Onwuka Shakira R , McIntosh Jennifer , Macrae Finlay , Chondros Patty , Boyd Lucy , Wijesuriya Rushani , Saya Sibel , Karnchanachari Napin , Novy Kitty , Jenkins Mark A , Walter Fiona M , Trevena Lyndal , Gutierrez Javiera Martinez , Broun Kate , Fishman George , Marker Julie , Emery Jon
Published: March 2024

Background

Australian guidelines recommend that people aged 50–70 years consider taking low-dose aspirin to reduce their risk of colorectal cancer (CRC).

Aim

To determine the effect of a consultation with a researcher before an appointment in general practice using a decision aid presenting the benefits and harms of taking low-dose aspirin compared with a general CRC prevention brochure on patients’ informed decision making and low-dose aspirin use.

Design and setting

Individually randomised controlled trial in six general practices in Victoria, Australia, from October 2020 to March 2021.

Method

Participants were recruited from a consecutive sample of patients aged 50–70 years attending a GP. The intervention was a consultation using a decision aid to discuss taking aspirin to reduce CRC risk while control consultations discussed reducing CRC risk generally. Self-reported co-primary outcomes were the proportion of individuals making informed choices about taking aspirin at 1 month and on low-dose aspirin uptake at 6 months, respectively. The intervention effect was estimated using a generalised linear model and reported with Bonferroni-adjusted 95% confidence intervals (CIs) and
P
-values.

Results

A total of 261 participants (86% of eligible patients) were randomised into trial arms (
n
= 129 intervention;
n
= 132 control). Of these participants, 17.7% (
n
= 20/113) in the intervention group and 7.6% (
n
= 9/118) in the control group reported making an informed choice about taking aspirin at 1 month, an estimated 9.1% (95% CI = 0.29 to 18.5) between-arm difference in proportions (odds ratio [OR] 2.47, 97.5% CI = 0.94 to 6.52,
P
= 0.074). The proportions of individuals who reported taking aspirin at 6 months were 10.2% (
n
= 12/118) of the intervention group versus 13.8% (
n
= 16/116) of the control group, an estimated between-arm difference of −4.0% (95% CI = −13.5 to 5.5; OR 0.68 [97.5% CI = 0.27 to 1.70,
P
= 0.692]).

Conclusion

The decision aid improved informed decision making but this did not translate into long-term regular use of aspirin to reduce CRC risk. In future research, decision aids should be delivered alongside various implementation strategies.
Clinical activity in general practice before sarcoma diagnosis: an Australian cohort study
Authors: Rafiq Meena , de Boer Jasper , Mar Jasmine , Desai Jayesh , Bae Susie , Gyorki David E , Di Bella Claudia , Lyratzopoulos Georgios , Lewin Jeremy H , Emery Jon
Published: March 2024

Background

Increased time to diagnosis in sarcoma is associated with poor prognosis and patient outcomes. Research is needed to identify whether opportunities to expedite the diagnosis of sarcoma in general practice exist.

Aim

To examine pre-diagnostic GP clinical activity before sarcoma diagnosis.

Design and setting

An Australian retrospective cohort study using hospital registry data (Australian Comprehensive Cancer Outcomes and Research Database [ACCORD]) linked to two primary care datasets (Patron and MedicineInsight).

Method

The frequency of general practice healthcare utilisation events (general practice attendances, prescriptions, blood test, and imaging requests) were compared in 377 patients with soft tissue sarcoma (STS) and 64 patients with bone sarcoma (BS) in the year pre-diagnosis. Poisson regression models were used to calculate monthly incidence rate ratios (IRR) for the 24 months pre-diagnosis and estimate inflection points for when healthcare use started to increase from baseline.

Results

In the 6 months pre-diagnosis, patients with sarcoma had a median of 3–4 general practice attendances, around one-third had a GP imaging request (33% [
n
= 21] BS and 36% [
n
= 134] STS), and approximately one in five had multiple imaging requests (19% [
n
= 12] BS and 21% [
n
= 80] STS). GP imaging requests progressively increased up to eight-fold from 6 months before sarcoma diagnosis (IRR 8.43, 95% confidence interval [CI] = 3.92 to 18.15,
P
<0.001) and general practice attendances increased from 3 months pre-diagnosis.

Conclusion

Patients with sarcoma have increased GP clinical activity from 6 months pre-diagnosis, indicating a diagnostic window where potential opportunities exist for earlier diagnosis. Interventions to help identify patients and promote appropriate use of imaging and direct specialist centre referrals could improve earlier diagnosis and patient outcomes.
Low Dimensional Multi Class Steganalysis of Spatial LSB based Stego Images Using Textural Features
Authors: Thanasekaran Veena , Selvaraj Arivazhagan
Published: March 2024

Image steganalysis ranges from detecting the presence of covert information in an image (passive steganalysis) to extraction of the information from the stego image (active steganalysis). One of the steps in active steganalysis is determining the stego algorithm used to produce the stego image. In this paper, a low dimensional combination of textural features is adapted for steganalysis. Also a novel blind statistical steganalyser to determine the spatial domain Least Significant Bit (LSB) based algorithms using one against one multi class classification is proposed. The proposed steganalyser is a multiclass ensemble Fisher Linear Discriminant (FLD) classifier that uses novel low dimensional textural features for steganalysis. The performed experiments on the Bossbase database for 5 different LSB based algorithms for 8 different payloads show that the results are much better than the state of art steganalyser.
Optimizing Machine Learning-based Sentiment Analysis Accuracy in Bilingual Sentences via Preprocessing Techniques
Authors: Maree Mohammed , Eleyat Mujahed , Mesqali Enas
Published: March 2024

With the recent advances in Natural Language Processing (NLP) technologies, the ability to process, analyze, and understand sentiments expressed in user-generated reviews regarding the products and services they use is becoming more achievable. Despite the latest improvements in this field, little attention has been given to multilingual sentiment analysis. In this article, a framework is presented for sentiment analysis in Arabic and English using two datasets (ASTD, AJGT) along with their translations. Preprocessing techniques, including n-gram tokenization, Arabic-specific stop words removal, punctuation removal, removing repeating characters, parts of speech tagging, stemming, and lemmatization, are applied. Four machine learning classifiers, namely Logistic Regression (LR), Random Forest (RF), Naive Bayes (NB), and Support Vector Machine (SVM), are employed. We highlight existing specialized research in sentiment analysis for Arabic and English, as well as the employed techniques in each. Furthermore, the impact of preprocessing on accuracy results for both Arabic and English languages is investigated through separate experiments for each step. Experimental results on the ASTD dataset demonstrate close performance across classifiers, with the SVM classifier achieving the highest accuracy of 70%. However, the accuracy varied when using the AJGT dataset, with the NB classifier yielding the best accuracy at approximately 87%. The experiments on the translated datasets from Arabic to English did not exhibit significant differences, although some features performed slightly better using the Arabic datasets.
Narrowing the Gap
Authors: Makridis Christos , Kuuskoski Jonathan
Published: March 2024

This paper investigates whether entrepreneurship training subsequently impacts artists’ labor market outcomes. Collecting data from major universities, we find that only 9.7% have arts entrepreneurship certificates; just 11.4% have any required arts entrepreneurship classes. Analyzing data from the American Community Survey (ACS) and controlling for demographic factors, fine arts graduates are 1.3% less likely to be employed and earn 8.7% lower annual earnings. However, individuals with both arts and entrepreneurial business training earn more and offset the earnings disadvantage by roughly a half. These results underscore the importance of integrating art entrepreneurship education with the sustainability of the arts sector.
Le Père Charles Plumier (1646 – 1704) : son oeuvre, son herbier de ptéridophytes américains. – 2. Typifications
Authors: Cremers Georges , Boudrie Michel , Viane Ronald , Aymonin Gérard Guy
Published: March 2024

Dans cette seconde partie de notre travail relatif à Plumier, nous procédons à l’analyse détaillée de ses planches iconographiques de ptéridophytes et de leur correspondance avec les spécimens d’herbier retrouvés à Paris (P, en particulier les herbiers du secteur historique). Par rapport aux descriptions des taxons pour lesquels Plumier était cité dans le protologue, des modifications et des compléments se sont avérés nécessaires comme, notamment, la désignation de 18 lectotypes (dont 5 de deuxième étape) et de 57 épitypes, la mise en évidence de synonymes nouveaux pour Hymenophyllum undulatum et la validation d’Hymenophyllum elegantulum comme taxon accepté. Des combinaisons nouvelles sont proposées : Amauropelta cruciata (Thelypteridaceae), Blotiella aurita (Dennstaedtiaceae), Pecluma struthionis et Pleopeltis x cuspidata (Polypodiaceae).