bluuebunny/crossref_metadata_2025 huggingface dataset:
Synthesis of Network Biobased Aliphatic Polyesters Exhibiting Better Tensile Properties than the Linear Polymers by ADMET Polymerization in the Presence of Glycerol Tris(undec-10-enoate)
Authors: Go Lance O’Hari P. , Abdellatif Mohamed Mehawed , Makino Ryoji , Shimoyama Daisuke , Higashi Seiji , Hirano Hiroshi , Nomura Kotohiro
Published: February 2024

Development of biobased aliphatic polyesters with better mechanical (tensile) properties in film has attracted considerable attention. This report presents the synthesis of soluble network biobased aliphatic polyesters by acyclic diene metathesis (ADMET) polymerization of bis(undec-10-enyl)isosorbide diester [M1, dianhydro-D-glucityl bis(undec-10-enoate)] in the presence of a tri-arm crosslinker [CL, glycerol tris(undec-10-enoate)] using a ruthenium–carbene catalyst, and subsequent olefin hydrogenation using RhCl(PPh3)3. The resultant polymers, after hydrogenation (expressed as HCP1) and prepared in the presence of 1.0 mol% CL, showed better tensile properties than the linear polymer (HP1) with similar molecular weight [tensile strength (elongation at break): 20.8 MPa (282%) in HP1 vs. 35.4 MPa (572%) in HCP1]. It turned out that the polymer films prepared by the addition of CL during the polymerization (expressed as a 2-step approach) showed better tensile properties. The resultant polymer film also shows better tensile properties than the conventional polyolefins such as linear high density polyethylene, polypropylene, and low density polyethylene.
Experimental Study of the Airflow Field and Fiber Motion in the Melt-Blowing Process
Authors: Wu Wenhan , Han Wanli , Sun Yafeng , Yi Honglei , Wang Xinhou
Published: February 2024

The melt-blowing process involves high velocity airflow and fiber motion, which have a significant effect on fiber attenuation. In this paper, the three-dimensional airflow field for a melt-blowing slot die was measured using the hot-wire anemometry in an experiment. The fiber motion was captured online using a high-speed camera. The characteristics of the airflow distribution and fiber motion were analyzed. The results show that the melt-blowing airflow field is asymmetrically distributed. The centerline air velocity is higher than that around it and decays quickly. The maximum airflow velocity exists near the die face, in the range of 130–160 m/s. In the region of −0.3 cm < y < 0.3 cm and 0 < z < 2 cm, the airflow has a high velocity (>100 m/s). As the distance of z reaches 5 cm and 7 cm, the maximum airflow velocity reduces to 70 m/s. The amplitude of fibers is calculated, and it increases with the increase in air dispersion area which has a significant influence on fiber attenuation. At z = 1.5 cm, 2.5 cm, 4 cm, and 5.5 cm, the average fiber amplitudes are 1.05 mm, 1.71 mm, 2.83 mm, and 3.97 mm, respectively. In the vicinity of the die, the fibers move vertically downward as straight segments. With the increase in distance from the spinneret, the fiber appears to bend significantly and forms a fiber loop. The fiber loop morphology affects the velocity of the fiber movement, causing crossover, folding, and bonding of the moving fiber. The study investigated the interaction between the fiber and airflow fields. It indicates that the airflow velocity, velocity difference, and dispersion area can affect the motion of fiber which plays an important role in fiber attenuation during the melt-blowing process.
Quantum Value Valuation Continuum
Authors: Özdilek Ünsal
Published: February 2024

Price, cost, and income (PCI) methods are traditionally used to approximate the value state of an economic commodity such as a property. Based on the estimates of these methods, we explore how quantum theory represents the fundamental process of value valuation in practice. We propose that the mathematical formalism of quantum theory is a promising view and measure of economic value. To ground our exploration, we first map traditional PCI estimates onto three-dimensional spherical coordinates, which were then transformed into two-dimensional quantum states using the Bloch sphere. This step enabled the computation of eigenvalues and eigenvectors of the Hamiltonian matrix, from which the value state measures were derived. The results exhibit practical applications as well as fundamental insights into potential connections between economic and quantum value states.
Photocatalytic TiO2-Based Nanostructures as a Promising Material for Diverse Environmental Applications: A Review
Authors: Gatou Maria-Anna , Syrrakou Athanasia , Lagopati Nefeli , Pavlatou Evangelia A.
Published: February 2024

Contemporary technological and industrial advancements have led to increased reliance on chemicals for product innovation, leading to heightened contamination of water sources by traditional pollutants (organic dyes, heavy metals) and disease-causing microorganisms. Wastewater treatment processes now reveal “emerging pollutants”, including pharmaceuticals, endocrine disruptors, and agricultural chemicals. While some are benign, certain emerging pollutants can harm diverse organisms. Researchers seek cost-effective water purification methods that completely degrade pollutants without generating harmful by-products. Semiconductor-based photocatalytic degradation, particularly using titanium dioxide (TiO2), is popular for addressing water pollution. This study focuses on recent applications of TiO2 nanostructures in photocatalysis for eliminating various water pollutants. Structural modifications, like doping and nanocomposite formation, enhance photocatalyst performance. The study emphasizes photocatalytic elimination mechanisms and comprehensively discusses factors impacting both the mechanism and performance of nano-TiO2-based photocatalysts. Characteristics of TiO2, such as crystal structure and energy band-gap, along with its photocatalytic activity mechanism, are presented. The review covers the advantages and limitations of different TiO2 nanostructure production approaches and addresses potential toxicity to human health and the environment. In summary, this review provides a holistic perspective on applying nano-TiO2 materials to mitigate water pollution.
Use of Biosourced Molecules as Liquid Organic Hydrogen Carriers (LOHC) and for Circular Storage
Authors: Bermudez Aponte Nelson Alexis , Meille Valérie
Published: February 2024

The use of Liquid Organic Hydrogen Carriers (LOHC) is one of the potential options to store hydrogen. Today, the vast majority of compounds used as LOHC come from the oil industry. Using biosourced LOHC would be a step forward in the development of this CO2-free solution. This article looks at LOHC candidates that can be obtained from biomass. The special case of formic acid and methanol, which do not fall within the definition of LOHC, is also considered. The synthesis of alcohols, polyols, amines, aminoalcohols and N-heterocyclic compounds from biosourced compounds is reviewed.
Coseismic Deformation Obtained by Various Technical Methods and Its Constraint Ability to Slip Models of Maduo Earthquake
Authors: Song Yujing , Qu Chunyan , Ma Chao , Shan Xinjian , Zhang Guohong , Chen Han , Wu Donglin
Published: February 2024

The coseismic deformation field on both sides of the fault, especially the distribution and change characteristics of near-field deformation, not only provides important constraints for the fine inversion of the slip distribution model but also serves as an important basis for the anti-disruption defense of the cross-fault linear engineering facilities. In this paper, we used Sentinel-1 satellite data to obtain the coseismic deformation field of the Maduo earthquake by using InSAR and offset techniques. We quantitatively compared the coseismic displacement of the three types of data: InSAR, offset, and optical images. The results show that optical images and offset provided more robust near-fault (<2 km) deformation insights than InSAR, which exhibited irregular deformation patterns due to incoherence near the fault. The maximum relative displacements for InSAR and offset observations are ~2.8 m and 4 m, respectively. Then we tested various fault slip models with different data constraints, revealing that a combined inversion of GPS, InSAR, and offset data offers superior constraints on slip distribution. This integrative approach effectively captured both shallow and deep fault slip, particularly near the fault zone. The eastern branch fault model, jointly constrained by GPS, InSAR, and offset data, is the optimal coseismic slip distribution model for the Maduo earthquake, and the maximum slip is 5.55 m.
A Novel Approach to Enhance Landslide Displacement Prediction with Finer Monitoring Data: A Case Study of the Baijiabao Landslide
Authors: Xia Ding , Tang Huiming , Glade Thomas
Published: February 2024

Rainfall and reservoir water level are commonly regarded as the two major influencing factors for reservoir landslides and are employed for landslide displacement prediction, yet their daily data are readily available with current monitoring technology, which makes a more refined analysis possible. However, until now, few efforts have been made to predict landslide displacements using daily data, which is likely to substantially improve accuracy and is crucial for landslide early warning. A novel feature enhancement approach for extracting critical characteristics from daily rainfall and reservoir water level data for use in landslide displacement prediction is proposed in this study. Six models, including gated recurrent units (GRUs), long short-term memory (LSTM), and support vector regression (SVR) with an unenhanced dataset and GRU-E, LSTM-E, and SVR-E with an enhanced dataset, were employed for displacement predictions at four GPS monitoring stations on the Baijiabao landslide, a typical step-like reservoir landslide. The results show that the accuracy values of all the enhanced models were significantly improved, and the GRU-E model achieved the most significant improvement, with the RMSE decreasing by 24.39% and R2 increasing by 0.2693, followed by the LSTM-E and SVR-E models. Further, the GRU-E model consistently outperformed the other models, achieving the highest R2 of 0.6265 and the lowest RMSE of 16.5208 mm, significantly superior than the others. This study indicates the feasibility of improving the accuracy of landslide monthly displacement predictions with finer monitoring data and provides valuable insights for future research.
The Variation Characteristics of Stratospheric Circulation under the Interdecadal Variability of Antarctic Total Column Ozone in Early Austral Spring
Authors: Li Jiayao , Zhou Shunwu , Guo Dong , Hu Dingzhu , Yao Yao , Wu Minghui
Published: February 2024

Antarctic Total Column Ozone (TCO) gradually began to recover around 2000, and a large number of studies have pointed out that the recovery of the Antarctic TCO is most significant in the austral early spring (September). Based on the Bodeker Scientific Filled Total Column Ozone and ERA5 reanalysis dataset covering 1979–2019, the variation characteristics of the Antarctic TCO and stratospheric circulation for the TCO ‘depletion’ period (1979–1999) and the ‘recovery’ period (2000–2019) are analyzed in September. Results show that: (1) Stratospheric elements significantly related to the TCO have corresponding changes during the two eras. (2) The interannual variability of the TCO and the above-mentioned stratospheric circulation elements in the recovery period are stronger than those in the depletion period. (3) Compared with the depletion period, due to the stronger amplitude of the planetary wave 1, stronger Eliassen–Palm (EP) flux corresponds to EP flux convergence, larger negative eddy heat flux, and positive eddy momentum flux in the stratosphere during the recovery period. The polar temperature rises in the lower and middle stratosphere and the polar vortex weakens in the middle and upper stratosphere, accompanied by the diminished area of PSC. This contributes to the understanding of Antarctic ozone recovery.
Enhancement of Vital Signals for UWB Through-Wall Radar Using Low-Rank and Block-Sparse Matrix Decomposition
Authors: Liang Xiao , Ye Shengbo , Song Chenyang , Kong Qingyang , Liu Xiaojun , Fang Guangyou
Published: February 2024

Ultra-wideband (UWB) vital detection radar plays an important role in post-disaster search and rescue, but the vital signal acquired in practice is often submerged in noise. In this paper, an advanced signal processing algorithm based on low-rank block-sparse representation is proposed to enhance the vital signal in life detection radar applications. The preprocessed echo signal can be decomposed into low-rank and block-sparse parts. The alternate direction method (ADM) is employed to obtain the block-sparse part containing the desired vital signal. We solve the subproblems involved in the ADM method using the Douglas/Peaceman–Rachford (DR) monotone operator splitting method. The projection method is applied to accelerate the calculation. Simulation and experimental results show that the proposed algorithm outperforms existing methods in terms of output signal-to-noise ratio (SNR).
A Robust Track Estimation Method for Airborne SAR Based on Weak Navigation Information and Additional Envelope Errors
Authors: Gao Ming , Qiu Xiaolan , Cheng Yao , Chen Min , Ding Chibiao
Published: February 2024

As miniaturization technology has progressed, Synthetic Aperture Radar (SAR) can now be mounted on Unmanned Aerial Vehicles (UAVs) to carry out observational tasks. Influenced by airflow, UAVs inevitably experience deviations or vibrations during flight. In the context of cost constraints, the precision of the measurement equipment onboard UAVs may be relatively low. Nonetheless, high-resolution imaging demands more accurate track information. It is therefore of great importance to estimate high-precision tracks in the presence of both motion and measurement errors. This paper presents a robust track estimation method for airborne SAR that makes use of both envelope and phase errors. Firstly, weak navigation information is employed for motion compensation, which reduces a significant portion of the motion error. Subsequently, the track is initially estimated using additional envelope errors introduced by the Extended Omega-K (EOK) algorithm. The track is then refined using a phase-based approach. Furthermore, this paper presents the calculation method of the compensated component for each target and provides an analysis of accuracy from both theoretical and simulation perspectives. The track estimation and imaging results in the simulations and real data experiments validate the effectiveness of the proposed method, with an estimation accuracy of real data experiments within 5 cm.
Submillimeter-Accurate Markerless Hand–Eye Calibration Based on a Robot’s Flange Features
Authors: Đalić Velibor , Jovanović Vedran , Marić Petar
Published: February 2024

An accurate and reliable estimation of the transformation matrix between an optical sensor and a robot is a key aspect of the hand–eye system calibration process in vision-guided robotic applications. This paper presents a novel approach to markerless hand–eye calibration that achieves streamlined, flexible, and highly accurate results, even without error compensation. The calibration procedure is mainly based on using the robot’s tool center point (TCP) as the reference point. The TCP coordinate estimation is based on the robot’s flange point cloud, considering its geometrical features. A mathematical model streamlining the conventional marker-based hand–eye calibration is derived. Furthermore, a novel algorithm for the automatic estimation of the flange’s geometric features from its point cloud, based on a 3D circle fitting, the least square method, and a nearest neighbor (NN) approach, is proposed. The accuracy of the proposed algorithm is validated using a calibration setting ring as the ground truth. Furthermore, to establish the minimal required number and configuration of calibration points, the impact of the number and the selection of the unique robot’s flange positions on the calibration accuracy is investigated and validated by real-world experiments. Our experimental findings strongly indicate that our hand–eye system, employing the proposed algorithm, enables the estimation of the transformation between the robot and the 3D scanner with submillimeter accuracy, even when using the minimum of four non-coplanar points for calibration. Our approach improves the calibration accuracy by approximately four times compared to the state of the art, while eliminating the need for error compensation. Moreover, our calibration approach reduces the required number of the robot’s flange positions by approximately 40%, and even more if the calibration procedure utilizes just four properly selected flange positions. The presented findings introduce a more efficient hand–eye calibration procedure, offering a superior simplicity of implementation and increased precision in various robotic applications.
Three-Dimensional Multi-Modality Registration for Orthopaedics and Cardiovascular Settings: State-of-the-Art and Clinical Applications
Authors: Garzia Simone , Capellini Katia , Gasparotti Emanuele , Pizzuto Domenico , Spinelli Giuseppe , Berti Sergio , Positano Vincenzo , Celi Simona
Published: February 2024

The multimodal and multidomain registration of medical images have gained increasing recognition in clinical practice as a powerful tool for fusing and leveraging useful information from different imaging techniques and in different medical fields such as cardiology and orthopedics. Image registration could be a challenging process, and it strongly depends on the correct tuning of registration parameters. In this paper, the robustness and accuracy of a landmarks-based approach have been presented for five cardiac multimodal image datasets. The study is based on 3D Slicer software and it is focused on the registration of a computed tomography (CT) and 3D ultrasound time-series of post-operative mitral valve repair. The accuracy of the method, as a function of the number of landmarks used, was performed by analysing root mean square error (RMSE) and fiducial registration error (FRE) metrics. The validation of the number of landmarks resulted in an optimal number of 10 landmarks. The mean RMSE and FRE values were 5.26 ± 3.17 and 2.98 ± 1.68 mm, respectively, showing comparable performances with respect to the literature. The developed registration process was also tested on a CT orthopaedic dataset to assess the possibility of reconstructing the damaged jaw portion for a pre-operative planning setting. Overall, the proposed work shows how 3D Slicer and registration by landmarks can provide a useful environment for multimodal/unimodal registration.
Data Fusion of Dual Foot-Mounted INS Based on Human Step Length Model
Authors: Chen Jianqiang , Liu Gang , Guo Meifeng
Published: February 2024

Pedestrian navigation methods based on inertial sensors are commonly used to solve navigation and positioning problems when satellite signals are unavailable. To address the issue of heading angle errors accumulating over time in pedestrian navigation systems that rely solely on the Zero Velocity Update (ZUPT) algorithm, it is feasible to use the pedestrian’s motion constraints to constrain the errors. Firstly, a human step length model is built using human kinematic data collected by the motion capture system. Secondly, we propose the bipedal constraint algorithm based on the established human step length model. Real field experiments demonstrate that, by introducing the bipedal constraint algorithm, the mean biped radial errors of the experiments are reduced by 68.16% and 50.61%, respectively. The experimental results show that the proposed algorithm effectively reduces the radial error of the navigation results and improves the accuracy of the navigation.
A High-Capacity Optical Metro Access Network: Efficiently Recovering Fiber Failures with Robust Switching and Centralized Optical Line Terminal
Authors: Ullah Rahat , Ullah Sibghat , Almadhor Ahmad , Alwageed Hathal Salamah , Al-Atawi Abdullah A. , Ren Jianxin , Chen Shuaidong
Published: February 2024

This study proposes and presents a new central office (CO) for the optical metro access network (OMAN) with an affordable and distinctive switching system. The CO’s foundation is built upon a novel optical multicarrier (OMC) generation technique. This technique provides numerous frequency carriers that are characterized by a high tone-to-noise ratio (TNR) of 40 dB and minimal amplitude excursions. The purpose is to accommodate multiple users at the optical network unit side in the optical metropolitan area network (OMAN). The OMC generation is achieved through a cascaded configuration involving a single phase and two Mach Zehnder modulators without incorporating optical or electrical amplifiers or filters. The proposed OMC is installed in the CO of the OMAN to support the 1.2 Tbps downlink and 600 Gbps uplink transmission, with practical bit error rate (BER) ranges from 10−3 to 10−13 for the downlink and 10−6 to 10−14 for the uplink transmission. Furthermore, in the OMAN’s context, optical fiber failure is a main issue. Therefore, we have proposed a possible solution for ensuring uninterrupted communication without any disturbance in various scenarios of main optical fiber failures. This demonstrates how this novel CO can rapidly recover transmission failures through robust switching a and centralized OLT. The proposed system is intended to provide users with a reliable and affordable service while maintaining high-quality transmission rates.
Research on Computing Resource Measurement and Routing Methods in Software Defined Computing First Network
Authors: Gong Xiaomin , Ren Shuangyin , Wang Chunjiang , Wang Jingchao
Published: February 2024

Computing resource measurement and computing routing are essential technologies in the computing first network (CFN), serving as its foundational elements. This paper introduces a Software Defined Computing First Network (SD-CFN) architecture. Building upon this framework, a Dynamic-Static Integrated Computing Resource Measurement Mechanism (DCRMM) is proposed, incorporating methods such as the entropy weight method and K-Means clustering. The DCRMM algorithm outperforms the Maximum-closest Static Algorithm (MSA) and Maximum Closest Dynamic Algorithm (MDA) in terms of node stability, node utilization, and node matching accuracy. Additionally, a Reinforcement Learning and Software Defined Computing First Networking Routing (RSCR) algorithm is presented as a software-defined computing routing solution within the SD-CFN. RSCR introduces a knowledge plane responsible for computing routing calculations. It comprehensively considers factors such as link latency, available bandwidth, and packet loss rate. Simulation experiments conducted on the GÉANT topology demonstrate that RSCR outperforms the OSPF algorithm in terms of link latency, packet loss rate, and throughput. DCRMM and RSCR offer innovative solutions for computing resource measurement and computing routing in computing first networks.
A High-Performance System for Weak ECG Real-Time Detection
Authors: Xu Kun , Yang Yi , Li Yu , Zhang Yahui , Zhang Limin
Published: February 2024

Wearable devices have been widely used for the home monitoring of physical activities and healthcare conditions, among which ambulatory electrocardiogram (ECG) stands out for the diagnostic cardiovascular information it contains. Continuous and unobtrusive sensing often requires the integration of wearable sensors to existing devices such as watches, armband, headphones, etc.; nonetheless, it is difficult to detect high-quality ECG due to the nature of low signal amplitude at these areas. In this paper, a high-performance system with multi-channel signal superposition for weak ECG real-time detection is proposed. Firstly, theoretical analysis and simulation is performed to demonstrate the effectiveness of this system design. The detection system, including electrode array, acquisition board, and the application (APP), is then developed and the electrical characteristics are measured. A common mode rejection ratio (CMRR) of up to 100 dB and input inferred voltage noise below 1 μV are realized. Finally, the technique is implemented in form of ear-worn and armband devices, achieving an SNR over 20 dB. Results are also compared with the simultaneous recording of standard lead I ECG. The correlation between the heart rates derived from experimental and standard signals is higher than 0.99, showing the feasibility of the proposed technique.
Assessing Cognitive Workload in Motor Decision-Making through Functional Connectivity Analysis: Towards Early Detection and Monitoring of Neurodegenerative Diseases
Authors: Cano Leonardo Ariel , Albarracín Ana Lía , Pizá Alvaro Gabriel , García-Cena Cecilia Elisabet , Fernández-Jover Eduardo , Farfán Fernando Daniel
Published: February 2024

Neurodegenerative diseases (NDs), such as Alzheimer’s, Parkinson’s, amyotrophic lateral sclerosis, and frontotemporal dementia, among others, are increasingly prevalent in the global population. The clinical diagnosis of these NDs is based on the detection and characterization of motor and non-motor symptoms. However, when these diagnoses are made, the subjects are often in advanced stages where neuromuscular alterations are frequently irreversible. In this context, we propose a methodology to evaluate the cognitive workload (CWL) of motor tasks involving decision-making processes. CWL is a concept widely used to address the balance between task demand and the subject’s available resources to complete that task. In this study, multiple models for motor planning during a motor decision-making task were developed by recording EEG and EMG signals in n=17 healthy volunteers (9 males, 8 females, age 28.66±8.8 years). In the proposed test, volunteers have to make decisions about which hand should be moved based on the onset of a visual stimulus. We computed functional connectivity between the cortex and muscles, as well as among muscles using both corticomuscular and intermuscular coherence. Despite three models being generated, just one of them had strong performance. The results showed two types of motor decision-making processes depending on the hand to move. Moreover, the central processing of decision-making for the left hand movement can be accurately estimated using behavioral measures such as planning time combined with peripheral recordings like EMG signals. The models provided in this study could be considered as a methodological foundation to detect neuromuscular alterations in asymptomatic patients, as well as to monitor the process of a degenerative disease.
The Role of Artificial Intelligence of Things in Achieving Sustainable Development Goals: State of the Art
Authors: Lampropoulos Georgios , Garzón Juan , Misra Sanjay , Siakas Kerstin
Published: February 2024

With the environmental and societal changes, the achievement of sustainable development goals (SDGs) and the realization of sustainability in general is now more important than ever. Through a bibliometric analysis and scientific mapping analysis, this study aims to explore and provide a review regarding the role of artificial intelligence (AI), the Internet of Things (IoT), and artificial intelligence of things (AIoT) in realizing sustainable development and achieving SDGs. AIoT can be defined as the combination of AI with IoT to create more efficient and data-driven interconnected, intelligent, and autonomous IoT systems and infrastructure that use AI methods and algorithms. The analysis involved 9182 documents from Scopus and Web of Science (WoS) from 1989 to 2022. Descriptive statistics of the related documents and the annual scientific production were explored. The most relevant and impactful authors, articles, outlets, affiliations, countries, and keywords were identified. The most popular topics and research directions throughout the years and the advancement of the field and the research focus were also examined. The study examines the results, discusses the main findings, presents open issues, and suggests new research directions. Based on the results of this study, AIoT emerged as an important contributor in ensuring sustainability and in achieving SDGs.
Selective and Accurate Detection of Nitrate in Aquaculture Water with Surface-Enhanced Raman Scattering (SERS) Using Gold Nanoparticles Decorated with β-Cyclodextrins
Authors: Li Zhen , Hu Yang , Wang Liu , Liu Houfang , Ren Tianling , Wang Cong , Li Daoliang
Published: February 2024

A surface-enhanced Raman scattering (SERS) method for measuring nitrate nitrogen in aquaculture water was developed using a substrate of β-cyclodextrin-modified gold nanoparticles (SH-β-CD@AuNPs). Addressing the issues of low sensitivity, narrow linear range, and relatively poor selectivity of single metal nanoparticles in the SERS detection of nitrate nitrogen, we combined metal nanoparticles with cyclodextrin supramolecular compounds to prepare a AuNPs substrate enveloped by cyclodextrin, which exhibits ultra-high selectivity and Raman activity. Subsequently, vanadium(III) chloride was used to convert nitrate ions into nitrite ions. The adsorption mechanism between the reaction product benzotriazole (BTAH) of o-phenylenediamine (OPD) and nitrite ions on the SH-β-CD@AuNPs substrate was studied through SERS, achieving the simultaneous detection of nitrate nitrogen and nitrite nitrogen. The experimental results show that BTAH exhibits distinct SERS characteristic peaks at 1168, 1240, 1375, and 1600 cm−1, with the lowest detection limits of 3.33 × 10−2, 5.84 × 10−2, 2.40 × 10−2, and 1.05 × 10−2 μmol/L, respectively, and a linear range of 0.1–30.0 μmol/L. The proposed method provides an effective tool for the selective and accurate online detection of nitrite and nitrate nitrogen in aquaculture water.
Echo-Level SAR Imaging Simulation of Wakes Excited by a Submerged Body
Authors: Jia Yan , Liu Shuyi , Liu Yongqing , Zhai Limin , Gong Yifan , Zhang Xiangkun
Published: February 2024

The paper introduces a numerical simulation method for Synthetic Aperture Radar (SAR) imaging of submerged body wakes by integrating hydrodynamics, electromagnetic scattering, and SAR imaging simulation. This work is helpful for better understanding SAR images of submerged body wakes. Among these, the hydrodynamic model consists of two sets of ocean dynamics closely related to SAR imaging, namely the wake of the submerged body and wind waves. For the wake, we simulated it using computational fluid dynamics (CFD) numerical methods. Furthermore, we compared and computed the electromagnetic scattering characteristics of wakes under various navigation parameters and sea surface conditions. Following that, based on the operational principles and imaging theory of synthetic aperture radar (SAR), we established the SAR raw echo signal of the wake. Employing a Range-Doppler (RD) algorithm, we generated simulated SAR images of the wake. The results indicate that utilizing Computational Fluid Dynamics (CFD) numerical methods enables the simulation of wake characteristics generated by the motion of a submerged body with different velocities. The backscattering features of wakes are closely associated with the relative orientation between the wake and the radar line of sight. Under specific wind speeds, the wake gets masked within the sea surface background, resulting in less discernible characteristics of the wake in SAR images. This suggests that at lower speeds of submerged body or under specific wind conditions, the detectability of the wake in SAR images significantly diminishes.
An End-to-End Inclination State Monitoring Method for Collaborative Robotic Drilling Based on Resnet Neural Network
Authors: Qian Lu , Liu Peifeng , Lu Hao , Shi Jian , Zhao Xingwei
Published: February 2024

The collaborative robot can complete various drilling tasks in complex processing environments thanks to the high flexibility, small size and high load ratio. However, the inherent weaknesses of low rigidity and variable rigidity in robots bring detrimental effects to surface quality and drilling efficiency. Effective online monitoring of the drilling quality is critical to achieve high performance robotic drilling. To this end, an end-to-end drilling-state monitoring framework is developed in this paper, where the drilling quality can be monitored through online-measured vibration signals. To evaluate the drilling effect, a Canny operator-based edge detection method is used to quantify the inclination state of robotic drilling, which provides the data labeling information. Then, a robotic drilling inclination state monitoring model is constructed based on the Resnet network to classify the drilling inclination states. With the aid of the training dataset labeled by different inclination states and the end-to-end training process, the relationship between the inclination states and vibration signals can be established. Finally, the proposed method is verified by collaborative robotic drilling experiments with different workpiece materials. The results show that the proposed method can effectively recognize the drilling inclination state with high accuracy for different workpiece materials, which demonstrates the effectiveness and applicability of this method.
Chemopreventive Potential of Oils Extracted from Seeds of Three Annona Species
Authors: Attanayake Prabash , Rupasinghe Dinesha , Gamage Ashoka , Madhujith Terrence , Merah Othmane
Published: February 2024

Annona fruit, leaves, seeds, roots, and bark have been conventionally used in many countries for medical treatments as they are considered ideal sources of pharmacologically active compounds, but Annona remains an underutilized fruit in many countries. The fruit of these plants is delicately flavored and is used in industrial products such as ready-to-serve beverages, wine, jellies, jam, and fruit-butter preserve, while the seeds generally go to waste. Annona seed oil contains numerous health-benefiting factors such as vitamins, minerals, bioactive compounds, fatty acids, antioxidants, and phenolic compounds, which are responsible for various biological activities, including antibacterial, antioxidant, and antitumor activities. Cancer is a worldwide major health problem that remains unresolved. Even though the current treatments can manage to reduce tumor growth, there is an urgent need to investigate more efficient but less expensive novel techniques to overcome some of the restrictions in treating tumors. Annona might offer an indispensable choice besides chemotherapy and radiotherapy, especially for terminally ill patients, as the Annona genus contains secondary metabolites in nearly every component of Annona plants. Research has shown that many Annona species contain promising components that could potentially exhibit anticancer activity, but the information available is scarce and inconsistent. Annona muricata (Soursop, “Katuanoda”), Annona squamosa (Sweetsop, “Seenianoda”), and Annona reticulata (Custard apple, “Welianoda”) are three commonly cultivated edible Annona species in Sri Lanka. The main objective of the review was to present an updated comprehensive literature analysis of the putative chemopreventive functions against cancer cell lines/the anticancer effect on cancers, phytochemical properties, and antioxidant properties possessed by the seed oils of three selected common Annona species. Although there are some in vitro and in vivo experimental investigations supporting the benefits of Annona seed oils, clinical investigations are still needed to explore concealed areas, determine the effects on the human body, determine the safest concentration, and determine health-contributing benefits before they are submitted to clinical trials.
The Cybersecurity Applied by Online Travel Agencies and Hotels to Protect Users’ Private Data in Smart Cities
Authors: Florido-Benítez Lázaro
Published: February 2024

The purpose of this paper is to analyse the cybersecurity in online travel agencies (OTAs) and hotel sectors to protect users’ private data in smart cities. Methodologically, this research uses a sample of information about cyberattacks that occurred during the period of 2000–2023 in companies operating as OTAs and in the travel, tourism, and food sectors, which was obtained from research articles. Then, we had to expand the research to include updated information about cyberattacks from digital newspapers, regulatory sources, and state data breach notification sites like CSIS, KonBriefing, EUROCONTROL, and GlobalData. The findings of the current research prove that hotels and OTAs were constantly exposed to cyberattacks in the period analysed, especially by data breaches and malware attacks; in fact, this is the main novelty of this research. In addition, these incidents were severe for both guests and tourism companies because their vulnerabilities and consequences affect the reputation of companies and smart cities where these firms operate, as well as consumer confidence. The results also showed that most of the cyberattacks examined in this manuscript were aimed at stealing information about the companies’ and users’ private data such as email addresses; credit card numbers, security codes, and expiration dates; and encoded magstripe data; among many other types of data. Cyberattacks and cyberthreats never disappear completely in the travel and tourism sectors because these illegal activities are closely related to the hacker’s thirst for power, fame, and wealth.
Investigating the Dynamics of Pedestrian Flow through Different Transition Bottlenecks
Authors: Mo Yurong , Qiu Shiyao , Tang Jiali , Li Zhihong
Published: February 2024

Congestion and queues are crucial factors in high-passenger flow areas, affecting both traffic efficiency and pedestrian comfort. Ensuring pedestrian safety in bottleneck areas is of utmost importance, and understanding flow characteristics is essential to improving resilience levels. In this study, a comparative experiment was conducted to investigate crowd dynamics in different transition bottleneck types, including straight, right-angle, and curve transitions. Pedestrian flow data were analyzed to examine the impact of transition shape on pedestrian characteristics, such as passing time, speeds, trajectories, and densities within the bottleneck. The results indicate that the curve bottleneck outperforms the other two types, significantly improving traffic capacity, particularly when the pedestrian rate ranges from 0.5 to 1.25 person/s. The curve bottleneck demonstrates the minimum passing time, lowest density, and fastest passing speed. Moreover, under various flow rates, the cumulative maximum pedestrian density of curve bottlenecks is consistently smaller than the other types. These findings offer valuable insights for designing and managing pedestrian flow in bottleneck areas to ensure safety and resilience levels.
From Likes to Sustainability: How Social Media Influencers Are Changing the Way We Consume
Authors: Vilkaite-Vaitone Neringa
Published: February 2024

Social media has become an integral part of our daily lives. Influencers have emerged as significant players in promoting sustainable consumption in recent years. With their reach and influence, they have the ability to sway consumer decisions and earn rewards from marketers. However, an influencer’s perceived importance and credibility among their followers is essential to their ability to persuade others. In this study, we utilized network theory and the theory of mind to scrutinize the impact of an influencer’s importance and credibility on sustainable consumption. We collected data from 427 consumers and conducted structural equation modeling (SEM) to test our hypotheses. Our findings indicate that an influencer’s importance has a positive impact on their credibility, which subsequently has a favorable impact on cognitive, affective, and conative sustainable consumption. These results confirm the importance and credibility of influencers in promoting sustainable consumption and provide insights into how social marketers and influencers can optimize their sustainable marketing strategies.
Soil CO2 and CH4 Dynamics and Their Relationships with Soil Nutrients, Enzyme Activity, and Root Biomass during Winter Wheat Growth under Shallow Groundwater
Authors: Zhang Wenchao , Guo Chen , Zhou Xinguo , Zhu Jianqiang , Li Fahu
Published: February 2024

Soil CO2 and CH4 concentrations are crucial determinants of crop physiology and the soil environment. However, the intricate relationships among soil respiration, soil nutrients, enzyme activities, and winter wheat growth in the presence of shallow groundwater remain enigmatic. This study aimed to investigate the dynamics of soil CO2 and CH4 concentrations and their correlations with soil nutrient content, enzymatic activities, and wheat root biomass to better understand the influence of shallow groundwater on soil environmental conditions. Lysimeter experiments were conducted at five groundwater depths (20, 40, 50, 60, and 80 cm) and three fertilizer application rates (low, 75%; normal, 100%; high, 125%). Soil CO2 (soil layer > 10 cm) and CH4 concentrations significantly decreased with increasing groundwater depth. The maximum values of root parameters and shoot biomass were mainly concentrated at 50–60 cm at the high fertilization level (except root length density, which was higher at the normal fertilization level), and were 0.36–77.4% higher than other treatments. Soil CO2 concentration showed positive correlations with organic matter and total N content, enzyme activities, and root biomass. Soil CH4 concentration had significant correlations with soil organic matter, total N, and available K. Compared to the fertilization level, groundwater depth emerged as a crucial factor as it affected soil physicochemical properties, soil enzymatic activities, root respiration, and winter wheat growth in shallow groundwater.
Employee Acceptance of Digital Transformation: A Study in a Smart City Context
Authors: Mutambik Ibrahim , Almuqrin Abdullah
Published: February 2024

The notion of the smart city offers significant benefits to citizens and enterprises alike. To realize these benefits, however, the city’s organizations and working processes need to undergo a digital transformation (DT) which reshapes work practices and demands a new mindset from city employees. The readiness of these employees to accept such a DT has an effect on the extent to which the city’s residents and businesses benefit from being in a smart city context. This raises the question of which factors have the most influence on employees’ acceptance of DT—a question that has thus far received limited attention from researchers. This study introduces a model that examines various influencing factors, using data collected from a survey of 1180 employees in 10 smart cities in Saudi Arabia. The factors examined take a variety of forms, including external elements such as management provision for employees and process complexity, which can lead to resistance to change, as well as internal elements, such as perceived advantages and inertia. The findings of the study show that management support for employees and the perceived advantages of DT have a positive relationship with acceptance by employees, while process complexity and inertia have a negative relationship with employees’ acceptance. These findings contribute to the growing body of literature concerning DT acceptance in a smart city context and will provide organizations with insights on which to base strategies for encouraging employee adaptation to evolving digital landscapes.
Sustainable Practices and Performance of Resource-Based Companies: The Role of Internal Control
Authors: Liu Xiao , Pan Huanxue , Lin Weixing , Wang Mengkai , Zhang Qiange
Published: February 2024

As the concept of sustainable resource usage gains popularity, resource-based companies are faced with the challenge of reconciling environmental responsibility with corporate performance to achieve the “coexistence” of environmental and economic benefits. We take data related to RBCs for 2010–2020 and perform a multiple regression analysis of the data. This study focuses on the role of internal control in analyzing the impact of resource-based companies (RBCs) on corporate financial performance (CFP) while assuming corporate environmental responsibility (CER). The findings reveal that the fulfillment of CER by RBCs positively impacts CFP. We then add a moderating test to observe the role of internal controls in the relationship between the two. The results show that the positive effect of CER on CFP is greater with stronger internal control measures. In addition, we introduce heterogeneity analysis to analyze the effect of firm ownership. The moderating effect is diminished in privately owned companies. This research provides empirical evidence for the moderating effect of internal control on the connection between CER and CFP while also considering the influence of ownership.
Towards Sustainable Early Education Practices: A Quasi-Experimental Study on the Effects of Kindergarten Physical Education Programs on Fundamental Movement Skills and Self-Regulation in Haikou City, China
Authors: Wu Hua , Eungpinichpong Wichai , Ruan Hui , Chen Wenke , Yang Yibei , Dong Xiujuan
Published: February 2024

Acquiring fundamental movement skills (FMS) in early childhood is linked to long-term engagement in physical activity, promoting lifelong health. Concurrently, the development of self-regulation contributes to fostering socially responsible and empathetic individuals. This study aims to contribute to the sustainable development goals of Good Health and Well-being (Goal 3) and Quality Education (Goal 4) by promoting early education practices that enhance children’s physical and socio-emotional development. This quasi-experimental study, employing a pre/post-test control design, examined the influence of different kindergarten physical education programs on FMS and self-regulation. Participants from a sports-themed kindergarten, ordinary public kindergarten, and non-profit private kindergarten were equally divided into three groups. The “Hello Sunshine” (HS) group followed a ball game-based program; the ordinary physical education (OPE) group’s curriculum had multi-themed physical activities; and the free-play (FP) group as a comparison group (free play) spent their activity time freely playing. Data from a total of 239 children were analyzed, all of whom received identical assessments of fundamental movement skills and self-regulation by the Test of Gross Motor Development-3 (TGMD-3) and the head–toes–knees–shoulders (HTKS) test at baseline and after 10 weeks of the PE curriculum. There was a significant effect of grouping on TGMD-3 composite scores after controlling for the pre-test score (F(2, 235) = 65.232, p < 0.001, Partial η2 = 0.357). The composite score of the HS group was clearly higher than that of the OPE (95% CI:10.72~16.45) and FP (95% CI: 4.16~9.98) groups. A significant group time effect was observed for self-regulation (F(2, 236) = 4.588, p = 0.011, Partial η2 = 0.037). After 10 weeks, the HS group displayed a more significant increase in self-regulation (14.8%) than that in the OPE (9.7%) and FP (14.6%) groups. The ball game-based program exhibited more advantages in promoting fundamental movement skills and self-regulation among the kindergarteners. Overall, this study’s findings highlight the potential benefits of kindergarten physical education programs and underscore the importance of early childhood development, emphasizing its potential to contribute to holistic child development and align with sustainability goals.