bluuebunny/crossref_metadata_2025 huggingface dataset:
Isomeric Aromatic Polyimides Containing Biphenyl Moieties for Gas Separation Applications
Authors: Matesanz-Niño Laura , Cuellas David , Aguilar-Lugo Carla , Palacio Laura , González-Ortega Alfonso , de la Campa José G. , Álvarez Cristina , Lozano Ángel E.
Published: March 2023

An optimized synthesis of the monomer 2,2′3,3′-biphenyltetracarboxylic dianhydride, iBPDA, was performed to obtain high molecular weight polymers. This monomer has a contorted structure that produces a non-linear shape, hindering the packing of the polymer chain. Aromatic polyimides of high molecular weight were obtained by reaction with the commercial diamine 2,2-bis(4-aminophenyl) hexafluoropropane, 6FpDA, which is a very common monomer in gas separation applications. This diamine has hexafluoroisopropylidine groups which introduce rigidity in the chains, hindering efficient packing. The thermal treatment of the polymers processed as dense membranes had two targets: on the one hand, to achieve the complete elimination of the solvent used, which could remain occluded in the polymeric matrix, and on the other hand to ensure the complete cycloimidization of the polymer. A thermal treatment exceeding the glass transition temperature was performed to ensure the maximum degree of imidization at 350 °C. The good mechanical properties of these materials allow for their use in high-pressure gas purification applications. Moreover, models of the polymers exhibited an Arrhenius-like behavior characteristic of secondary relaxations, normally associated with local motions of the molecular chain. The gas productivity of these membranes was high.
Criteria for Assessing Sustainability of Lignocellulosic Wastes: Applied to the Cellulose Nanofibril Packaging Production in the UK
Authors: Islam Samantha , Cullen Jonathan M.
Published: March 2023

Extensive use of petrochemical plastic packaging leads to the greenhouse gas emission and contamination to soil and oceans, posing major threats to the ecosystem. The packaging needs, hence, are shifting to bioplastics with natural degradability. Lignocellulose, the biomass from forest and agriculture, can produce cellulose nanofibrils (CNF), a biodegradable material with acceptable functional properties, that can make packaging among other products. Compared to primary sources, CNF extracted from lignocellulosic wastes reduces the feedstock cost without causing an extension to agriculture and associated emissions. Most of these low value feedstocks go to alternative applications, making their use in CNF packaging competitive. To transfer the waste materials from current practices to the packaging production, it is imperative to assess their sustainability, encompassing environmental and economic impacts along with the feedstock physical and chemical properties. A combined overview of these criteria is absent in the literature. This study consolidates thirteen attributes, delineating sustainability of lignocellulosic wastes for commercial CNF packaging production. These criteria data are gathered for the UK waste streams, and transformed into a quantitative matrix, evaluating the waste feedstock sustainability for CNF packaging production. The presented approach can be adopted to decision scenarios in bioplastics packaging conversion and waste management.
Effects of Electron Beam Irradiation on Mechanical and Tribological Properties of PEEK
Authors: Kurbanova Bayan , Aimaganbetov Kazybek , Ospanov Kanat , Abdrakhmanov Kairat , Zhakiyev Nurkhat , Rakhadilov Bauyrzhan , Sagdoldina Zhuldyz , Almas Nurlan
Published: March 2023

In this work, the mechanical and tribological characteristics of polyetheretherketone (PEEK) sheets were enhanced by electron beam irradiation. PEEK sheets irradiated at a speed of 0.8 m/min with a total dose of 200 kGy achieved the lowest specific wear rate of 4.57 ± 0,69 (10−6 mm3/N−1m−1), compared to unirradiated PEEK with a rate of 13.1 ± 0.42 (10−6 mm3/N−1m−1). Exposure to an electron beam at 9 m/min for 30 runs, with a dose of 10 kGy per run for a total dose of 300 kGy, resulted in the highest improvement in microhardness, reaching 0.222 GPa. This may be due to the decrease in crystallite size, as indicated by the broadening of the diffraction peaks in the irradiated samples. According to the results of thermogravimetric analysis, the degradation temperature of the irradiated samples remained unchanged at 553 ± 0.5 °C, except a sample irradiated at dose 400 kGy, where the degradation temperature shifted towards a lower position of 544 ± 0.5 °C. Differential scanning calorimetry results revealed that the melting temperature () of the unirradiated PEEK was about 338 ± 0.5 °C, while a high temperature shift of the was observed for the irradiated samples.
Effect of Aging on Unidirectional Composite Laminate Polyethylene for Body Armor
Authors: Engelbrecht-Wiggans Amy , Tsinas Zois , Krishnamurthy Ajay , Forster Amanda L.
Published: March 2023

The construction of ballistic-resistant body armor is experiencing an increasing use of flexible unidirectional (UD) composite laminates that comprise multiple layers. Each UD layer contains hexagonally packed high-performance fibers with a very low modulus matrix (sometimes referred to as binder resins). Laminates are then made from orthogonal stacks of these layers, and these laminate-based armor packages offer significant performance advantages over standard woven materials. When designing any armor system, the long-term reliability of the armor materials is critical, particularly with regard to stability with exposure to temperature and humidity, as these are known causes of degradation in commonly used body armor materials. To better inform future armor designers, this work investigates the tensile behavior of an ultra-high molar mass polyethylene (UHMMPE) flexible UD laminate that was aged for at least 350 d at two accelerated conditions: 70 °C at 76% relative humidity (RH) and 70 °C in a desiccator. Tensile tests were performed at two different loading rates. The mechanical properties of the material after ageing demonstrated less than 10% degradation in tensile strength, indicating high reliability for armor made from this material.
Neutron Stress Measurement of W/Ti Composite in Cryogenic Temperatures Using Time-of-Flight Method
Authors: Nishida Masayuki , Harjo Stefanus , Kawasaki Takuro , Yamashita Takayuki , Gong Wu
Published: March 2023

In this study, the thermal stress alterations generated in a tungsten fiber reinforced titanium composite (W/Ti composite) were evaluated by the neutron stress measurement method at cryogenic temperatures. The W/Ti composite thermal loads were repeated from room temperature to the cryogenic temperature (10 K), and alterations in thermal residual stress were evaluated using the neutron in situ stress measurement method. In this measurement, the stress alterations in the titanium matrix and the tungsten fibers were measured. This measurement was carried out by TAKUMI (MLF-BL19) of J-PARC, a neutron research facility in the Japan Atomic Agency. The measurement method of TAKUMI is the time-of-flight (TOF) method. Owing to this measurement method, the measurement time was significantly shortened compared to the angle-dispersion type measurement by a diffractometer. As a result of the measurement, large compressive stresses of about 1 GPa were generated in the tungsten fibers, and tensile stresses of about 100 MPa existed in the titanium matrix. The thermal stresses due to the temperature change between room temperature and cryogenic temperature is caused by the difference of thermal expansions between the tungsten fibers and the titanium matrix, and these stress values can be approximated by a simple elastic theory equation.
Estrogen Receptor Knockout Mice and Their Effects on Fertility
Authors: Nalvarte Ivan , Antonson Per
Published: March 2023

Estrogens play a crucial role in sexual development and fertility as well as many other physiological processes, and it is estrogen receptors that mediate the physiological responses. To study the role of the estrogen receptors in these processes, several genetic mouse models have been developed using different strategies, which also in some cases yield different results. Here, we summarize the models that have been made and their impact on fertility in relation to known cases of human estrogen receptor mutations.
Transitus: The Discontinuity and Death of Religious Communities in the Twenty-First Century
Authors: Pansters Krijn
Published: March 2023

In religious community life, the question of one’s own finitude in the perspective of the infinite is always at play, but communities are now really having to let go of organizational and spiritual patterns on the one hand and develop new ones on the other. Probably clearer than anywhere else in the world, the decades-long exodus of organized religious life can be seen and felt in the Netherlands and Belgium, where centuries-old congregations are now being dissolved and their monasteries repurposed. In this article, I will study the phenomenon of religious discontinuity and death from five analytical perspectives: historical, sociological, organizational, psychological, and theological. An overall perspective is that of “transitus spirituality”, of individual ways (as well as inabilities) to experience a form of completion and find closure when dealing with the discomforting fact of collective discontinuity and corporate death, of the (imminent) end of one’s own community. I will conclude with a reflection on the future of organized religious life.
Theology of Greek-Byzantine Church Fathers as a Specific Way of Philosophical Thinking in an Epistemological Context
Authors: Chistyakova Olga , Chistyakov Denis
Published: March 2023

The article presents the theological ideas and mystical–religious teachings of the Greek-Byzantine Church Fathers, which, at the same time, are philosophical because Byzantine theologians also reflected on human and their life, on the relationship between man and God, on the possibilities of God-cognition and obtaining higher sacred knowledge. Based on the analysis of the anthropological and epistemological ideas of the Greek Church Fathers, we highlight that philosophizing was always at the heart of Byzantine theology. Therefore, the Byzantine tradition of the Church Fathers is considered a unique type of philosophy of religion, which originated in the historical formation of the Christian faith in the era of the Triadic and Christological theological debates of the 4th to 7th centuries. This article reflects the teachings of three of the brightest thinkers-theologians of Byzantium—John Climacus, Maximus the Confessor, and Symeon the New Theologian. Their teachings are the foundation and main source of the mystical–religious tradition of Byzantine theology and philosophy. John Climacus’s conception of human self-improvement and self-cognition on the path of theosis is revealed as one of the first philosophical and moral systems of early Byzantium and the source of subsequent Christian concepts of Eastern Christianity. Maximus the Confessor’s conception of the logoi—or energies—of God is presented as a system of symbols with profound philosophical and anthropological meaning. The human being in St. Maximus’s doctrine is the main and self-sufficient symbol of the universe, connecting the two worlds—the Divine and the earthly ones. The doctrine of Symeon the New Theologian on uncreated light is revealed as a personal comprehension of God in the perception of Divine Light. The transforming power of the Light is demonstrated, which changes the nature of a human being and raises an individual to the height of spiritual unity with God. Finally, conclusions are made about the beginning and formation of the philosophy of religion as a special type of philosophical–religious thinking found already in the period of early Christianity.
The Myth of Secular Philosophy: Philosophy of Religion’s Origin and Fate
Authors: Loncar Samuel
Published: March 2023

Philosophy of religion (PoR) embodies the crisis and contradiction of the modern separation of reason and religion. The false assumption that reason is linked to the secular, and that religion is inferior to science or philosophy, creates a challenging situation for the field of PoR. This article shows how the split of reason and religion takes life in a secularization story, the myth of secular philosophy, that PoR implicitly challenges by its very existence. By making explicit the institutional uniqueness of PoR and showing how it challenges the myth of secular philosophy, the article argues that PoR embodies an alternative, and truer, vision of philosophy in which global diversity and inclusion is part of the very essence of the philosophical project.
Research Perspectives in Collaborative Assembly: A Review
Authors: Yonga Chuengwa Thierry , Swanepoel Jan Adriaan , Kurien Anish Matthew , Kanakana-Katumba Mukondeleli Grace , Djouani Karim
Published: March 2023

In recent years, the emergence of Industry 4.0 technologies has introduced manufacturing disruptions that necessitate the development of accompanying socio-technical solutions. There is growing interest for manufacturing enterprises to embrace the drivers of the Smart Industry paradigm. Among these drivers, human–robot physical co-manipulation of objects has gained significant interest in the literature on assembly operations. Motivated by the requirement for human dyads between the human and the robot counterpart, this study investigates recent literature on the implementation methods of human–robot collaborative assembly scenarios. Using a combination of strings, the researchers performed a systematic review search, sourcing 451 publications from various databases (Science Direct (253), IEEE Xplore (49), Emerald (32), PudMed (21) and SpringerLink (96)). A coding assignment in Eppi-Reviewer helped screen the literature based on ‘exclude’ and ‘include’ criteria. The final number of full-text publications considered in this literature review is 118 peer-reviewed research articles published up until September 2022. The findings anticipate that research publications in the fields of human–robot collaborative assembly will continue to grow. Understanding and modeling the human interaction and behavior in robot co-assembly is crucial to the development of future sustainable smart factories. Machine vision and digital twins modeling begin to emerge as promising interfaces for the evaluation of tasks distribution strategies for mitigating the actual human ergonomic and safety risks in collaborative assembly solutions design.
A Unified Formulation for the Computation of the Six-Degrees-of-Freedom-Motion-Induced Errors in Floating Doppler Wind LiDARs
Authors: Salcedo-Bosch Andreu , Farré-Guarné Joan , Araújo da Silva Marcos Paulo , Rocadenbosch Francesc
Published: March 2023

This work presents an analytical formulation to assess the six-degrees-of-freedom-motion-induced error in floating Doppler wind LiDARs (FDWLs). The error products derive from the horizontal wind speed bias and apparent turbulence intensity. Departing from a geometrical formulation of the FDWL attitude and of the LiDAR retrieval algorithm, the contributions of the rotational and translational motion to the FDWL-measured total error are computed. Central to this process is the interpretation of the velocity–azimuth display retrieval algorithm in terms of a first-order Fourier series. The obtained 6 DoF formulation is validated numerically by means of a floating LiDAR motion simulator and experimentally in nearshore and open-sea scenarios in the framework of the Pont del Petroli and IJmuiden campaigns, respectively. Both measurement campaigns involved a fixed and a floating ZephIRTM 300 LiDAR. The proposed formulation proved capable of estimating the motion-induced FDWL horizontal wind speed bias and returned similar percentiles when comparing the FDWL with the fixed LiDAR. The estimations of the turbulence intensity increment statistically matched the FDWL measurements under all motional and wind scenarios when clustering the data as a function of the buoy’s mean tilt amplitude, mean translational-velocity amplitude, and mean horizontal wind speed.
Center-Ness and Repulsion: Constraints to Improve Remote Sensing Object Detection via RepPoints
Authors: Gao Lei , Gao Hui , Wang Yuhan , Liu Dong , Momanyi Biffon Manyura
Published: March 2023

Remote sensing object detection is a basic yet challenging task in remote sensing image understanding. In contrast to horizontal objects, remote sensing objects are commonly densely packed with arbitrary orientations and highly complex backgrounds. Existing object detection methods lack an effective mechanism to exploit these characteristics and distinguish various targets. Unlike mainstream approaches ignoring spatial interaction among targets, this paper proposes a shape-adaptive repulsion constraint on point representation to capture geometric information of densely distributed remote sensing objects with arbitrary orientations. Specifically, (1) we first introduce a shape-adaptive center-ness quality assessment strategy to penalize the bounding boxes having a large margin shift from the center point. Then, (2) we design a novel oriented repulsion regression loss to distinguish densely packed targets: closer to the target and farther from surrounding objects. Experimental results on four challenging datasets, including DOTA, HRSC2016, UCAS-AOD, and WHU-RSONE-OBB, demonstrate the effectiveness of our proposed approach.
Information Fusion for Spaceborne GNSS-R Sea Surface Height Retrieval Using Modified Residual Multimodal Deep Learning Method
Authors: Wang Qiang , Zheng Wei , Wu Fan , Zhu Huizhong , Xu Aigong , Shen Yifan , Zhao Yelong
Published: March 2023

Traditional spaceborne Global Navigation Satellite Systems Reflectometry (GNSS-R) sea surface height (SSH) retrieval methods have the disadvantages of complicated error models, low retrieval accuracy, and difficulty using full DDM information. To compensate for these deficiencies while considering the heterogeneity of the input data, this paper proposes an end-to-end Modified Residual Multimodal Deep Learning (MRMDL) method that can utilize the entire range of DDM information. First, the MRMDL method is constructed based on the modified Residual Net (MResNet) and Multi-Hidden layer neural network (MHL-NN). The MResNet applicable to DDM structures is used to adaptively capture productive features of the full DDM and to convert the two-dimensional DDM data into one-dimensional numerical form. Then, the extracted features and auxiliary parameters are fused as the input data for MHL-NN to retrieve the SSH. Second, the reliability of the model is verified using SSH with tide-corrected DTU Sea Surface Height 18 (DTU18) and spaceborne radar altimeters (Jason3, HY-2C, HY-2B). Compared to the SSH provided by the DTU18 validation model and the spaceborne radar altimeter, the Pearson correlation coefficients (PCC) are 0.98 and 0.97, respectively. However, the CYGNSS satellite is not primarily employed for ocean altimetry, and the mean absolute differences (MAD) are 3.92 m and 4.32 m, respectively. Finally, the retrieval accuracy of the MRMDL method and the HALF retracking approach are compared and analyzed. Finally, this study also implements the HALF retracking algorithm to derive the SSH, and the results are compared with those computed by the MRMDL method. The MRMDL method is more accurate than the HALF retracking approach according to MAD, Root-Mean-Square Error (RMSE), and PCC, with an improvement of 35.21%, 17.25%, and 2.08%, respectively. The MRMDL method will contribute a new theoretical and methodological reference for future GNSS-R altimetry satellites with high spatiotemporal SSH retrieval.
A Global Remote-Sensing Assessment of the Intersite Variability in the Greening of Coastal Dunes
Authors: Petrova Petya G. , de Jong Steven M. , Ruessink Gerben
Published: March 2023

In recent decades, the vegetation on many coastal dunes has expanded spatially, which is attributed, among other things, to global-scale climate change. The intersite variability in this dune greening has not yet been substantially investigated, nor is it known whether it is consistent with intersite variability in climate change. Therefore, the objectives of this work were firstly to quantify and analyse the change in vegetation cover from multitemporal NDVI time series at a large number (186) of dune fields worldwide, calculated from Landsat satellite imagery available between 1984 and 2021 and secondly, to correlate the identified trends with trends in the main climate variables influencing vegetation growth (temperature, precipitation and wind speed). We show that greening is strongest in cool temperate climates (35° to 66.5° north/south latitudes) and that the rate of greening is accelerating at many sites. We find no dependence between the rate of greening and the local temporal change in temperature, precipitation and/or wind speed. Based on existing literature, sand supply and anthropogenic activities are discussed as possible reasons for the absence of a clear global relationship between variability in dune greening and climate change.
Slow Deformation Time-Series Monitoring for Urban Areas Based on the AWHPSPO Algorithm and TELM: A Case Study of Changsha, China
Authors: Xing Xuemin , Zhang Jihang , Zhu Jun , Zhang Rui , Liu Bin
Published: March 2023

Health monitoring is important for densely distributed urban infrastructures, particularly in cities undergoing rapid economic progress. Permanent scatterer interferometry (PSI) is an advanced remote sensing observation technique that is commonly used in urban infrastructure monitoring. However, the rapid construction of infrastructures may easily cause a loss of coherence for radar interferometry, inducing a low density of effective permanent scatterer (PS) points, which is the main limitation of PSI. In order to address these problems, a novel time-series synthetic aperture radar interferometry (InSAR) process based on the adaptive window homogeneous pixel selection and phase optimization (AWHPSPO) algorithm and thermal expansion linear model (TELM) is proposed. Firstly, for homogeneous point selection, information on both the time-series intensity and deformation phases is considered, which can compensate for the defects of insufficient homogeneous samples and low phase quality in traditional distributed scatterer interferometric synthetic aperture radar (DS-InSAR) processing. Secondly, the physical, thermal expansion component, which reflects the material properties of the infrastructures, is introduced into the traditional linear model, which can more rationally reflect the temporal evolution of deformation variation, and the thermal expansion coefficients can be estimated simultaneously with the deformation parameters. In order to verify our proposed algorithm, the Orange Island area in Changsha City, China, was selected as the study area in this experiment. Three years of its historical time-series deformation fields and thermal expansion coefficients were regenerated. With the use of high-resolution TerraSAR-X radar satellite images, a maximum accumulated settlement of 12.3 mm and a minor uplift of 8.2 mm were detected. Crossvalidation with small baseline subset interferometric synthetic aperture radar (SBAS-InSAR) results using Sentinel 1A data proved the reliability of AWHPSPO. The proposed algorithm can provide a reference for the control of the health and safety of urban infrastructures.
Multi-Stage Network for Event-Based Video Deblurring with Residual Hint Attention
Authors: Kim Jeongmin , Jung Yong Ju
Published: March 2023

Video deblurring aims at removing the motion blur caused by the movement of objects or camera shake. Traditional video deblurring methods have mainly focused on frame-based deblurring, which takes only blurry frames as the input to produce sharp frames. However, frame-based deblurring has shown poor picture quality in challenging cases of video restoration where severely blurred frames are provided as the input. To overcome this issue, recent studies have begun to explore the event-based approach, which uses the event sequence captured by an event camera for motion deblurring. Event cameras have several advantages compared to conventional frame cameras. Among these advantages, event cameras have a low latency in imaging data acquisition (0.001 ms for event cameras vs. 10 ms for frame cameras). Hence, event data can be acquired at a high acquisition rate (up to one microsecond). This means that the event sequence contains more accurate motion information than video frames. Additionally, event data can be acquired with less motion blur. Due to these advantages, the use of event data is highly beneficial for achieving improvements in the quality of deblurred frames. Accordingly, the results of event-based video deblurring are superior to those of frame-based deblurring methods, even for severely blurred video frames. However, the direct use of event data can often generate visual artifacts in the final output frame (e.g., image noise and incorrect textures), because event data intrinsically contain insufficient textures and event noise. To tackle this issue in event-based deblurring, we propose a two-stage coarse-refinement network by adding a frame-based refinement stage that utilizes all the available frames with more abundant textures to further improve the picture quality of the first-stage coarse output. Specifically, a coarse intermediate frame is estimated by performing event-based video deblurring in the first-stage network. A residual hint attention (RHA) module is also proposed to extract useful attention information from the coarse output and all the available frames. This module connects the first and second stages and effectively guides the frame-based refinement of the coarse output. The final deblurred frame is then obtained by refining the coarse output using the residual hint attention and all the available frame information in the second-stage network. We validated the deblurring performance of the proposed network on the GoPro synthetic dataset (33 videos and 4702 frames) and the HQF real dataset (11 videos and 2212 frames). Compared to the state-of-the-art method (D2Net), we achieved a performance improvement of 1 dB in PSNR and 0.05 in SSIM on the GoPro dataset, and an improvement of 1.7 dB in PSNR and 0.03 in SSIM on the HQF dataset.
Original and Low-Cost ADS-B System to Fulfill Air Traffic Safety Obligations during High Power LIDAR Operation
Authors: Peyrin Frédéric , Fréville Patrick , Montoux Nadège , Baray Jean-Luc
Published: March 2023

LIDAR is an atmospheric sounding instrument based on the use of high-power lasers. The use of these lasers involves fulfilling obligations with respect to air safety. In this article, we present a low-cost air traffic surveillance solution integrated into an automated operating system for the Rayleigh-Mie-Raman LIDAR of Clermont Ferrand and the statistical elements of its application over more than two years of operation from September 2019 to March 2022. Air traffic surveillance that includes the possibility of shutting off lasers is required by international regulations because LIDAR is equipped with a class four laser that presents potential dangers to aircraft flying overhead. The original system presented in this article is based on software-defined radio. ADS-B transponder frames are analyzed in real-time, and laser emission is stopped during LIDAR operation when an aircraft is detected within a 2 km radius around the LIDAR. The system was accredited in 2019 by the French air traffic authorities. Laser shutdowns due to the detection of aircraft near the Clermont Ferrand LIDAR caused a data loss rate of less than 2% during the period of application.
Dioxepine-Peri-Annulated PMIs—Synthesis and Spectral and Sensing Properties
Authors: Zagranyarski Yulian , Cheshmedzhieva Diana Valentinova , Mutovska Monika , Ahmedova Anife , Stoyanov Stanimir
Published: March 2023

New perylene monoimide (PMI) derivatives bearing a seven-membered heterocycle and 1,8-diaminosarcophagine (DiAmSar) or N,N-dimethylaminoethyl chelator fragments were synthesized, and their spectroscopic properties in the absence and presence of metal cations were determined to evaluate their potential applications as PET optical sensors for such analytes. DFT and TDDFT calculations were employed to rationalize the observed effects.
Suppression of Common-Mode Resonance in Multiband Base Station Antennas
Authors: Farasat Madiha , Thalakotuna Dushmantha , Yang Yang , Hu Zhonghao , Esselle Karu
Published: March 2023

5G demands a significant increment in the number of connected devices. As a result, gNodeBs are constantly pushed to serve more spectrum and smaller sectors. These increased capacity demands are met by using multiband antennas in base stations. One of the key challenges with multiband antennas is the pattern distortions due to the presence of other surrounding antenna element structures. This work provides a novel approach to address the challenge of pattern distortion in the lower frequency band 690–960 MHz due to common-mode (CM) currents in the high- frequency-band antenna element operating in the 1810–2690 MHz band. A common-mode suppression circuit is integrated with the impedance matching network of the high-band antenna element to reduce these common-mode currents. The experimental results verified that the common-mode suppression circuit reduces the common-mode currents at low-band frequencies by moving the common-mode resonance frequency outside the low frequency band, resulting in cleaner low-band patterns meeting pattern specifications.
Investigation on Modulation-Based Straightness Measurement
Authors: Egidi Andrea , Balsamo Alessandro , Corona Davide , Pisani Marco
Published: March 2023

The concept of a novel non-contacting technique for measuring straightness and its practical realization in a mechanical device are presented in this article. The device, called InPlanT, is based on the acquisition of the luminous signal retroreflected by a spherical glass target and impinged on a photodiode after mechanical modulation. The received signal is reduced to the sought straightness profile using dedicated software. The system was characterized with a high-accuracy CMM and the maximum error of indication was derived.
A Critical Review of Remote Sensing Approaches and Deep Learning Techniques in Archaeology
Authors: Kadhim Israa , Abed Fanar M.
Published: March 2023

To date, comprehensive reviews and discussions of the strengths and limitations of Remote Sensing (RS) standalone and combination approaches, and Deep Learning (DL)-based RS datasets in archaeology have been limited. The objective of this paper is, therefore, to review and critically discuss existing studies that have applied these advanced approaches in archaeology, with a specific focus on digital preservation and object detection. RS standalone approaches including range-based and image-based modelling (e.g., laser scanning and SfM photogrammetry) have several disadvantages in terms of spatial resolution, penetrations, textures, colours, and accuracy. These limitations have led some archaeological studies to fuse/integrate multiple RS datasets to overcome limitations and produce comparatively detailed outcomes. However, there are still knowledge gaps in examining the effectiveness of these RS approaches in enhancing the detection of archaeological remains/areas. Thus, this review paper is likely to deliver valuable comprehension for archaeological studies to fill knowledge gaps and further advance exploration of archaeological areas/features using RS along with DL approaches.
State of Charge Estimation Model Based on Genetic Algorithms and Multivariate Linear Regression with Applications in Electric Vehicles
Authors: Manriquez-Padilla Carlos Gustavo , Cueva-Perez Isaias , Dominguez-Gonzalez Aurelio , Elvira-Ortiz David Alejandro , Perez-Cruz Angel , Saucedo-Dorantes Juan Jose
Published: March 2023

Nowadays, the use of renewable, green/eco-friendly technologies is attracting the attention of researchers, with a view to overcoming recent challenges that must be faced to guarantee the availability of Electric Vehicles (EVs). Therefore, this work proposes a methodology based on Genetic Algorithms (GA) and multivariate regression for estimating and modeling the State of Charge (SOC) in Electric Vehicles. Indeed, the proposal considers the continuous monitoring of six load-related variables that have an influence on the SOC (State of Charge), specifically, the vehicle acceleration, vehicle speed, battery bank temperature, motor RPM, motor current, and motor temperature. Thus, these measurements are evaluated in a structure comprised of a Genetic Algorithm and a multivariate regression model in order to find those relevant signals that better model the State of Charge, as well as the Root Mean Square Error (RMSE). The proposed approach is validated under a real set of data acquired from a self-assembly Electric Vehicle, and the obtained results show a maximum accuracy of approximately 95.5%; thus, this proposed method can be applied as a reliable diagnostic tool in the automotive industry.
Sensitiveness of Variables Extracted from a Fitness Smartwatch to Detect Changes in Vertical Impact Loading during Outdoors Running
Authors: Pirscoveanu Cristina-Ioana , Oliveira Anderson Souza
Published: March 2023

Accelerometry is becoming a popular method to access human movement in outdoor conditions. Running smartwatches may acquire chest accelerometry through a chest strap, but little is known about whether the data from these chest straps can provide indirect access to changes in vertical impact properties that define rearfoot or forefoot strike. This study assessed whether the data from a fitness smartwatch and chest strap containing a tri-axial accelerometer (FS) is sensible to detect changes in running style. Twenty-eight participants performed 95 m running bouts at ~3 m/s in two conditions: normal running and running while actively reducing impact sounds (silent running). The FS acquired running cadence, ground contact time (GCT), stride length, trunk vertical oscillation (TVO), and heart rate. Moreover, a tri-axial accelerometer attached to the right shank provided peak vertical tibia acceleration (PKACC). The running parameters extracted from the FS and PKACC variables were compared between normal and silent running. Moreover, the association between PKACC and smartwatch running parameters was accessed using Pearson correlations. There was a 13 ± 19% reduction in PKACC (p < 0.005), and a 5 ± 10% increase in TVO from normal to silent running (p < 0.01). Moreover, there were slight reductions (~2 ± 2%) in cadence and GCT when silently running (p < 0.05). However, there were no significant associations between PKACC and the variables extracted from the FS (r < 0.1, p > 0.05). Therefore, our results suggest that biomechanical variables extracted from FS have limited sensitivity to detect changes in running technique. Moreover, the biomechanical variables from the FS cannot be associated with lower limb vertical loading.
Photothermal Quotient Describes the Combined Effects of Heat and Shade Stresses on Canola Seed Productivity
Authors: Rivelli Gonzalo M. , Gomez Nora V. , Mantese Anita I. , Miralles Daniel J. , Abeledo Leonor G. , Rondanini Deborah P.
Published: March 2023

There is evidence of the negative effects on canola seed yield caused by shading (SH) and high temperature stress (HT) separately, but the combined effect of both stresses has not been studied. This work aimed to (i) evaluate the effects of SH and HT stresses, alone and combined, on floral development, seed yield and quality, (ii) quantify the resulting effect (additive, synergistic, antagonistic) of combined stresses, and (iii) examine the utility of the photothermal quotient (PTQ, solar radiation/temperature ratio) to predict seed yield in stressed canola crops. Two field experiments were performed in Buenos Aires (Argentina) applying HT daytime temperature stress (25–30 °C from 1000 to 1500 h), SH (−80% irradiance), and SH + HT combined stresses, with C unstressed (20 °C and 100% irradiance) crops. Long and short duration SH and HT strongly affected floral development (fewer flowers and pods, with smaller ovules) and seed yield (reduction from −40 to −90% respect to C). Combined SH + HT exhibited detrimental synergistic effects on seed yield and oil concentration for long duration stresses, whereas antagonistic effects were mainly observed for short stresses. We conclude that the PTQ (cumulative from 100 to 500 °Cd after flowering) summarizes adequately the detrimental effects of combined post-flowering abiotic stresses on canola seed productivity.
“Never Learned to Love Properly”: A Qualitative Study Exploring Romantic Relationship Experiences in Adult Children of Narcissistic Parents
Authors: Lyons Minna , Brewer Gayle , Hartley Anna-Maria , Blinkhorn Victoria
Published: March 2023

Narcissism is a personality trait characterised by selfishness, coldness, entitlement, and grandiosity. There has been much research on different parenting dimensions and their relationship to narcissism in grown-up children, with a notable lack of studies investigating the influence of narcissistic parents on their children. This study focused on individuals’ experiences in romantic relationships, using personal narratives from a popular ‘Reddit’ community for people who perceived to have grown up with narcissistic parents. Using an inductive thematic analysis on 77 Reddit posts, we identified four themes: (i) Strategies and emotions in current relationships, (ii) behaviours and characteristics of partners and their families, (iii) parent intrusiveness in current relationships, and (iv) journey to realisation and recovery. Themes are discussed in relation to existing literature and theory. We add to the sparse literature on narcissistic parents’ influence in adult relationships, highlighting the importance of process from parental behaviour to adult romantic relationships.
System Dynamics Modeling for Assessing the Impact of COVID-19 on Food Supply Chains: A Case Study of Kenya and Rwanda
Authors: Tonnang Henri E. Z. , Sokame Bonoukpoè Mawuko , Wamalwa Mark , Niassy Saliou , Muriithi Beatrice Wambui
Published: March 2023

Disruptions in the food supply chains caused by the COVID-19 pandemic have destabilized the balance between production, supply, transport, distribution, and consumption. Consequently, these disruptions have affected food and nutritional security all over the world. This study proposes a framework for investigating the impact of COVID-19 on food supply chains, considering Eastern Africa as a focus region with Kenya and Rwanda as case studies. A systems thinking approach with three systemic components (food and nutrition, COVID-19 contagion, and human health) was applied. The contagion component was characterized by the susceptible, exposed, infected, recovered, and deceased (SEIRD) epidemiological modeling method. We then applied a causal loop diagram and stock and flow diagrams to map the links and interactions between variables from the contagion, health, and food supply chain components of the whole system. The results reveal that COVID-19 has adversely affected food and nutritional security in Eastern African countries. Key response measures to COVID-19 such as lockdowns, closure of borders, isolation, and quarantining have resulted in labor shortages, increased unemployment rates, loss of income, and the subsequent contraction of economies. The disruption of the food supply chain has negatively impacted the main pillars of food and nutrition security, which are availability, accessibility, utilization, and stability. We suggest direct food supply from local producers to the consuming communities to shorten the food supply chain and therefore enhance food self-sufficiency to reduce the severe effects of COVID-19 on food and nutrition security. Overall, our study provides a useful framework to help design better policies and build more resilient and inclusive food systems during COVID-19 and similar pandemics in the future.
Sustainability of Using Steel Fibers in Reinforced Concrete Deep Beams without Stirrups
Authors: Almasabha Ghassan , Murad Yasmin , Alghossoon Abdullah , Saleh Eman , Tarawneh Ahmad
Published: March 2023

Reinforced Concrete (RC) deep beams perform better structurally when steel fibers are added, as this reduces the need for web steel reinforcements, boosts shear strength, and helps to bridge cracks. The current ACI 318-19 code does not include predicting shear strength models to account for the added steel fibers in Steel Fibers Reinforced Concrete (SFRC) deep beams without stirrups; therefore, structural engineers are less motivated to use them. To fill this gap, the databases of 281 RC and 172 SFRC deep beams were compiled, and the preliminary investigation of the collected databases revealed that (1) Longitudinal steel reinforcement significantly increases the shear strength of SFRC specimens, as the steel fibers make deep beams better at carrying loads by assisting them in bridging cracks; and (2) Although shear stress and span-to-depth ratio are inversely related, SFRC deep beams encounter larger shear loads than RC deep beams because when the span-to-depth ratio of beams increases, the failure mode switches from crushing struts to diagonal shear failure. To help structural engineers adopt SFRC deep beams, a nonlinear regression-based model was developed to estimate the shear strength of SFRC deep beams using the experimental database of SFRC beams. Three factors—feature selection, data preprocessing, and model development—were considered. Additionally, the model’s effectiveness was evaluated and compared with other models found in the literature. The proposed shear strength model of SFRC performed better than the other models in the literature, providing the lowest Root Mean Square Error (RMSE) of 1.58 MPa. The results of this study give practitioners a strong platform for establishing precise and useful estimations of shear strength in SFRC deep beams without stirrups.
The Impact of E-Leadership Competencies on Workplace Well-Being and Job Performance: The Mediating Role of E-Work Self-Efficacy
Authors: Alkhayyal Shatha , Bajaba Saleh
Published: March 2023

Teleworking is a new business reality that entails adapting leadership styles to function effectively in a virtual environment. Technologically enabled leadership, or e-leadership, is promising for the telework norm. However, studies on e-leadership are in the early stages. Inspired by this need and drawing insight from social cognitive theory, this study explores the mediating role of e-work self-efficacy in the relationship between e-leadership competencies and workplace well-being and job performance. Data from 269 teleworkers worldwide were analyzed using partial least squares path modeling (PLS-PM). The findings show that e-worker self-efficacy partially mediates the relationship between e-leadership competencies and workplace well-being and fully mediates the relationship between e-leadership competencies and job performance. A teleworker-friendly business model can be achieved by equipping e-leaders with competencies that will enhance the employee’s self-efficacy and performance. A discussion of the findings, contributions, limitations, and future directions is provided.
Integrating Unsupervised Machine Intelligence and Anomaly Detection for Spatio-Temporal Dynamic Mapping Using Remote Sensing Image Series
Authors: Gino Vinícius L. S. , Negri Rogério G. , Souza Felipe N. , Silva Erivaldo A. , Bressane Adriano , Mendes Tatiana S. G. , Casaca Wallace
Published: March 2023

The synergistic use of remote sensing and unsupervised machine learning has emerged as a potential tool for addressing a variety of environmental monitoring applications, such as detecting disaster-affected areas and deforestation. This paper proposes a new machine-intelligent approach to detecting and characterizing spatio-temporal changes on the Earth’s surface by using remote sensing data and unsupervised learning. Our framework was designed to be fully automatic by integrating unsupervised anomaly detection models, remote sensing image series, and open data extracted from the Google Earth Engine platform. The methodology was evaluated by taking both simulated and real-world environmental data acquired from several imaging sensors, including Landsat-8 OLI, Sentinel-2 MSI, and Terra MODIS. The experimental results were measured with the kappa and F1-score metrics, and they indicated an assertiveness level of 0.85 for the change detection task, demonstrating the accuracy and robustness of the proposed approach when addressing distinct environmental monitoring applications, including the detection of disaster-affected areas and deforestation mapping.
Adsorption of Tetracycline by Magnetic Mesoporous Silica Derived from Bottom Ash—Biomass Power Plant
Authors: Hanh Phan Thi Hong , Phoungthong Khamphe , Chantrapromma Suchada , Choto Patcharanan , Thanomsilp Chuleeporn , Siriwat Piyanuch , Wisittipanit Nuttachat , Suwunwong Thitipone
Published: March 2023

In recent years, the contamination of the aquatic environment with antibiotics, including tetracyclines, has drawn much attention. Bottom ash (BA), a residue from the biomass power plant, was used to synthesize the magnetic mesoporous silica (MMS) and was utilized as an adsorbent for tetracycline (TC) removal from aqueous solutions. The MMS was characterized by Fourier transform-infrared (FTIR), X-ray diffraction (XRD) pattern, and scanning electron microscopy (SEM). Optimum conditions were obtained in overnight incubation at 60 °C, a pH of 6–8, and an adsorption capacity of 276.74 mg/g. The isotherm and kinetic equations pointed to a Langmuir isotherm model and pseudo-first-order kinetic optimum fitting models. Based on the very low values of entropy changes (ΔS°), the negative value of enthalpy changes (ΔH°) (−15.94 kJ/mol), and the negative Gibbs free-energy changes (ΔG°), the adsorption process was physisorption and spontaneous.
Mindfulness Abilities Are Associated with Anxiety Levels, Emotional Intelligence, and Perceived Self-Efficacy
Authors: Martínez-Pérez Inés , García-Rodríguez Almudena , Morales-Rodríguez Francisco Manuel , Pérez-Mármol José Manuel
Published: March 2023

This study examined the relationship between anxiety, emotional intelligence, perceived self-efficacy, and mindfulness abilities. A total of 205 Spanish university students were assessed for mindfulness (Freiburg Mindfulness Inventory-14), state-trait anxiety (State-Trait Anxiety Inventory), emotional intelligence (Trait Meta-Mood Scale-24), and general perceived self-efficacy (General Self-Efficacy Scale). The Student’s t-test was used to evaluate the possible differences between sexes for the study variables. Multiple regression analyses were conducted for each sex independently to evaluate the relationship between mindfulness and the other psychological variables, using mindfulness dimensions as a dependent variable. The results showed significant differences between females and males in mindfulness dimensions of self-control (p < 0.001) and acceptance (p = 0.012), and state (p = 0.005) and trait anxiety (p < 0.001). Multiple linear regression analyses revealed that the models for the relationship between mindfulness dimensions (attention, self-control, acceptance, and self-perception) and the other variables differed between females and males. Our results suggest that anxiety, emotional intelligence, and general perceived self-efficacy may be related to mindfulness abilities among a sample of Spanish university students. These findings could inform the development of targeted intervention programs to improve these psycho-emotional abilities.