bluuebunny/crossref_metadata_2025 huggingface dataset:
Effects of MgSO4 Alone or Associated with 4-PBA on Behavior and White Matter Integrity in a Mouse Model of Cerebral Palsy: A Sex- and Time-Dependent Study
Authors: Legouez Lou , Le Dieu-Lugon Bérénice , Feillet Shérine , Riou Gaëtan , Yeddou Melissa , Plouchart Thibault , Dourmap Nathalie , Le Ray Marie-Anne , Marret Stéphane , Gonzalez Bruno J. , Cleren Carine
Published: December 2022

Cerebral palsy (CP) is defined as permanent disorders of movement and posture. Prematurity and hypoxia–ischemia (HI) are risk factors of CP, and boys display a greater vulnerability to develop CP. Magnesium sulfate (MgSO4) is administered to mothers at risk of preterm delivery as a neuroprotective agent. However, its effectiveness is only partial at long term. To prolong MgSO4 effects, it was combined with 4-phenylbutyrate (4-PBA). A mouse model of neonatal HI, generating lesions similar to those reported in preterms, was realized. At short term, at the behavioral and cellular levels, and in both sexes, the MgSO4/4-PBA association did not alter the total prevention induced by MgSO4 alone. At long term, the association extended the MgSO4 preventive effects on HI-induced motor and cognitive deficits. This might be sustained by the promotion of oligodendrocyte precursor differentiation after HI at short term, which led to improvement of white matter integrity at long term. Interestingly, at long term, at a behavioral level, sex-dependent responses to HI were observed. This might partly be explained by early sex-dependent pathological processes that occur after HI. Indeed, at short term, apoptosis through mitochondrial pathways seemed to be activated in females but not in males, and only the MgSO4/4-PBA association seemed to counter this apoptotic process.
Vibrational Analysis of Hydration-Layer Water around Ubiquitin, Unpeeled Layer by Layer: Molecular-Dynamics Perceptions
Authors: Martinez-Gonzalez José Angel , Nandi Prithwish K. , English Niall J. , Gowen Aoife
Published: December 2022

Classical molecular-dynamics simulations have been performed to examine the interplay between ubiquitin and its hydration-water sub-layers, chiefly from a vibrational-mode and IR viewpoint—where we analyse individual sub-layers characteristics. The vibrational Density of States (VDOS) revealed that the first solvation sub-shell indicates a confined character therein. For layers of increasing distance from the surface, the adoption of greater bulk-like spectral behaviour was evident, suggesting that vibrational harmonisation to bulk occurs within 6–7 Å of the surface.
Spinal Cord Injury Causes Marked Tissue Rearrangement in the Urethra—Experimental Study in the Rat
Authors: Ferreira Ana , Chambel Sílvia Sousa , Avelino António , Cruz Célia Duarte
Published: December 2022

Traumatic spinal cord injury (SCI) results in the time-dependent development of urinary impairment due to neurogenic detrusor overactivity (NDO) and detrusor-sphincter-dyssynergia (DSD). This is known to be accompanied by massive changes in the bladder wall. It is presently less clear if the urethra wall also undergoes remodelling. To investigate this issue, female rats were submitted to complete spinal transection at the T8/T9 level and left to recover for 1 week and 4 weeks. To confirm the presence of SCI-induced NDO, bladder function was assessed by cystometry under urethane anesthesia before euthanasia. Spinal intact animals were used as controls. Urethras were collected and processed for further analysis. Following thoracic SCI, time-dependent changes in the urethra wall were observed. Histological assessment revealed marked urethral epithelium reorganization in response to SCI, as evidenced by an increase in epithelial thickness. At the muscular layer, SCI resulted in strong atrophy of the smooth muscle present in the urethral sphincter. Innervation was also affected, as evidenced by a pronounced decrease in the expression of markers of general innervation, particularly those present in sensory and sympathetic nerve fibres. The present data show an evident impact of SCI on the urethra, with significant histological rearrangement, accompanied by sensory and sympathetic denervation. It is likely that these changes will affect urethral function and contribute to SCI-induced urinary dysfunction, and they deserve further investigation.
Carotenoid-Enriched Nanoemulsions and γ-Rays Synergistically Induce Cell Death in a Novel Radioresistant Osteosarcoma Cell Line
Authors: Russo Maria , Moccia Stefania , Spagnuolo Carmela , Tedesco Idolo , Russo Gian Luigi
Published: December 2022

We previously demonstrated that SAOS human osteosarcoma cells, incubated with carotenoid-enriched nanoemulsions (CEN), activated a nonprotective form of autophagy and delayed cell proliferation. The present work focuses on the biological effects of CEN on a derivative of SAOS cells named SAOS400, recently described for their radiation resistance and higher expression of therapy-induced senescence (TIS) markers. SAOS400 cells, incubated with CEN, activated a “cytostatic” form of autophagy confirmed by cell cycle arrest in the G2/M phase and increased expression of autophagic proteins. Treatment of SAOS400 cells with CEN also resulted in decreased expression of the senescence marker p16INK4. However, when SAOS400 cells were γ-irradiated in combination with CEN, the threshold for cell death was reached (>60% after 96 h). We showed that this type of cell death corresponded to ‘cytotoxic’ or ‘lethal’ autophagy and that the combined treatment of CEN plus γ-rays was synergistic, with the combination index < 1. Since CEN contained β-carotene, the pure compound was used in SAOS400 cells at the same concentration present in CEN and up to 10 times higher. However, no radio-sensitizing effect of β-carotene was observed, suggesting that the biological effect of CEN was due to less abundant but more bioactive molecules, or to the synergistic activity of multiple components present in the extracts, confirming the functional pleiotropy of natural extracts enriched in bioactive molecules.
Shikimate Kinase Plays Important Roles in Anthocyanin Synthesis in Petunia
Authors: Yuan Junwei , Zhong Shiwei , Long Yu , Guo Jingling , Yu Yixun , Liu Juanxu
Published: December 2022

In plants, the shikimate pathway is responsible for the production of aromatic amino acids L-tryptophan, L-phenylalanine, and L-tyrosine. L-Phenylalanine is the upstream substrate of flavonoid and anthocyanin synthesis. Shikimate kinase (SK) catalyzes the phosphorylation of the C3 hydroxyl group of shikimate to produce 3-phosphate shikimate (S3P), the fifth step of the shikimate pathway. However, whether SK participates in flavonoid and anthocyanin synthesis is unknown. This study characterized the single-copy PhSK gene in the petunia (Petunia hybrida) genome. PhSK was localized in chloroplasts. PhSK showed a high transcription level in corollas, especially in the coloring stage of flower buds. Suppression of PhSK changed flower color and shape, reduced the content of anthocyanins, and changed the flavonoid metabolome profile in petunia. Surprisingly, PhSK silencing caused a reduction in the shikimate, a substrate of PhSK. Further qPCR analysis showed that PhSK silencing resulted in a reduction in the mRNA level of PhDHQ/SDH, which encodes the protein catalyzing the third and fourth steps of the shikimate pathway, showing a feedback regulation mechanism of gene expression in the shikimate pathway.
Examining the Effects of Mirror Therapy on Psychological Readiness and Perception of Pain in ACL-Injured Female Football Players
Authors: D’Isanto Tiziana , D’Elia Francesca , Esposito Giovanni , Altavilla Gaetano , Raiola Gaetano
Published: December 2022

Virtual reality-guided imagery (VRGI) and mirror therapy (MT) have been used in isolation to treat patients suffering from different injuries. However, no attempts have been made to understand the effects of combined VRGI and MT added to conventional physical therapy, and no information exists regarding perceptual responses to these rehabilitation strategies in female football players. Thus, this study aimed to examine the effect of MT added to conventional rehabilitation on psychological readiness and perception of pain in ACL-injured female football players. Thirty ACL-injured female football players competing in the 2nd and 3rd Italian tier who underwent an ACL rehabilitation program from the same clinic participated in this study. Players were randomly distributed in an MT group (n = 15) and a CON group (n = 15). All participants reported their perception of pain on a VAS before and after the interventions and their psychological readiness to return to sport after ACL injury and reconstruction surgery on the ACL-RSI scale after the intervention. An independent-sample t-test was performed to assess between-group differences in post-intervention ACL-RSI, and a further independent-sample t-test to assume non-significant differences between VAS values before the intervention. A two-way repeated-measures analysis of variance was used to test the null hypothesis of no different change in VAS over time between groups. After the intervention, the MT group perceived largely greater psychological readiness (p < 0.01). MT and CON groups experienced a large reduction in VAS after the intervention (p < 0.001). However, a small time × group interaction was observed (p = 0.023). MT reported a greater perception of the psychological readiness of the soccer players and a lower perception of pain than those who performed conventional therapy.
Pivot Step Jump: A New Test for Evaluating Jumping Ability in Young Basketball Players
Authors: Theodorou Apostolos S. , Rizou Hariklia-Parthenia , Zacharakis Emmanouil , Ktistakis Ioannis , Bekris Evangelos , Panoutsakopoulos Vassilios , Strouzas Panagiotis , Bourdas Dimitrios I. , Kostopoulos Nikolaos
Published: December 2022

Jumping ability in basketball is usually assessed using standardized vertical jump tests. However, they lack specificity and do not consider the player’s basketball skills. Several studies have suggested performing specific jump tests, which are tailored to the movement patterns and requirements of a basketball game. The pivot step jump test (PSJT) is a novel test designed to evaluate the specific jumping abilities of basketball players by combining a pivot step on one leg with a maximum bilateral vertical jump. This study had two aims: to determine the reliability and validity of the PSJT using typical jump tests as the criterion measure and to demonstrate the PSJT as a practical test to evaluate specific jumping ability in young male and female basketball players. Twenty female (EGA; 14.0 ± 0.7 years, 59.3 ± 7.9 kg, 162.1 ± 5.5 cm) and fifteen male (EGB; 14.0 ± 0.7 years, 58.1 ± 7.7 kg, 170.3 ± 6.4 cm) basketball players participated in the study. The test–retest reliability of the PSJT within sessions (intrasession reliability) and across sessions (intersession reliability) was assessed within EGA. For the evaluation of validity, EGB performed the PSJT and a series of criterion jumping tests. For EGA, no changes (p > 0.05) were found in PSJT performance between test sessions and excellent intra- and intersession reliability was observed (ICCs > 0.75). Correlation coefficients indicated high factorial validity between the jumping tests and PSJT (r = 0.71–0.91, p < 0.001). The PSJT appears to offer a valid assessment of jumping ability in basketball and is a practical test for assessing sport-specific jumping skills in young basketball players.
Predicting Wheat Leaf Nitrogen Content by Combining Deep Multitask Learning and a Mechanistic Model Using UAV Hyperspectral Images
Authors: Ma Xiao , Chen Pengfei , Jin Xiuliang
Published: December 2022

Predicting leaf nitrogen content (LNC) using unmanned aerial vehicle (UAV) images is of great significance. Traditional LNC prediction methods based on empirical and mechanistic models have limitations. This study aimed to propose a new LNC prediction method based on combining deep learning methods and mechanistic models. Wheat field experiments were conducted to make plants with different LNC values. The LNC and UAV hyperspectral images were collected during the critical growth stages of wheat. Based on these data, a method combining the deep multitask learning method and the N-based PROSAIL model was proposed and compared with traditional LNC prediction methods, including spectral index (SI), partial least squares regression (PLSR) and artificial neural network (ANN) methods. The results show that the new proposed method obtained the best LNC prediction results, with R2, RMSE and RMSE% values of 0.79, 20.86 μg/cm2 and 18.63%, respectively, during calibration and 0.82, 18.40 μg/cm2 and 16.92%, respectively, during validation. The other methods obtained R2, RMSE and RMSE% values between 0.29 and 0.68, 25.71 and 38.52 μg/cm2 and 22.95 and 34.39%, respectively, during calibration and between 0.43 and 0.74, 22.79 and 33.55 μg/cm2 and 20.96 and 30.86%, respectively, during validation. Thus, this study provides an accurate LNC prediction tool for precise nitrogen (N) management in the field.
Diverse Geological Evolution of Impact Basins on the Moon
Authors: Deng Jiayin , Cheng Weiming , Jiao Yimeng
Published: December 2022

Impact basins are the dominant landforms on the lunar surface, and their geological evolution varies. This research studied the diversity in the geological evolution of three impact basins: the Dirichlet–Jackson Basin, the Nectaris Basin, and the Orientale Basin. First, the regional topography and geomorphology of the three basins were studied using the SLDEM2015 digital elevation model (DEM). Clementine ultraviolet–visible (UVVIS) data and Moon Mineralogy Mapper (M3) data were used to study the chemical composition and mineralogical composition of the three basins. Additionally, the lunar crust thickness data have been used to study the subsurface structure of the three basins. The topographical analogies of the three basins indicate that the shapes of the basins are cavity-like. However, the shape of the Dirichlet–Jackson basin is not an obvious cavity compared with the other basins. The positions with minimum and maximum crustal thickness of the three basins are located at the center and the rim. The uplift of the crust-mantle interface of the Nectaris Basin and Orientale Basin is relatively larger than in the Dirichlet–Jackson Basin. Below the center of the maria of the Nectaris Basin and Orientale Basin, collapses occurred at the crust–mantle interface. The concentrations of FeO and TiO2 in the non-mare formation of the basin and maria show expected bimodal distributions. Moreover, we found exposures of olivine-rich materials in the Nectaris Basin and Orientale Basin which are located in the Rosse and Maunder craters, respectively. These exposures of olivine may be explained by the fact that the formation of the large impact basin, which might penetrate and blast away the upper lunar crust, excavating deep-seated material.
Research on UWB Indoor Positioning Algorithm under the Influence of Human Occlusion and Spatial NLOS
Authors: Zhang Hao , Wang Qing , Yan Chao , Xu Jiujing , Zhang Bo
Published: December 2022

Ultra-wideband (UWB) time-of-flight (TOF)-based ranging information in a non-line-of-sight (NLOS) environment can display significant forward errors, which directly affect positioning performance. NLOS has been a major factor limiting the improvement of UWB positioning accuracy and its application in complex scenarios. Therefore, in order to weaken the influence of the indoor complex environment on the NLOS environment of UWB and to further improve the performance of positioning, in this paper, we first analyze the factors and characteristics of NLOS formation in an indoor environment. The NLOS is divided into fixed NLOS influenced by spatial structure and dynamic random NLOS influenced by human occlusion. Then, the anchor LOS/NLOS information map is established by making full use of indoor spatial a priori information. On this basis, a robust adaptive extended Kalman filtering algorithm based on the anchor LOS/NLOS information map is designed, which is not only effectively able to exclude the influence of spatial NLOS, but can also optimize the random error. The proposed algorithm was validated in different experimental scenarios. The experimental results show that the positioning accuracy is better than 0.32 m in complex indoor NLOS environments.
Longitudinal Evolution of Storm-Enhanced Densities: A Case Study
Authors: Li Bo , Le Huijun , Li Wenbo , Chen Yiding , Liu Libo
Published: December 2022

Due to the limitations on observational data, most storm-enhanced density (SED) studies have focused on the North American sector. The complete picture of the longitudinal evolution of SEDs is still not clear. In this study, we investigated the dynamic evolution of SEDs from the European sector to the North American sector during a geomagnetic storm that occurred on the 15 July 2012, the main phase of which lasted nearly 30 h, maintaining the stable interplanetary magnetic field (IMF) and solar wind input conditions. Multiple data sets were analyzed, including convection data from the Super Dual Auroral Radar Network (SuperDARN), total electron contents (TECs) from the Madrigal database, plasma data from the Millstone Hill incoherent scatter radar (MHISR), solar wind and geomagnetic indices from OMNIWeb, and regional auroral electrojet indices from SuperMAG. The observations showed that the positions of SEDs shifted from local noon over the European sector towards dusk over the American sector and simultaneously moved to lower latitudes. The peak values of SED TECs were found to be greater in the European sector and to decrease with universal time. A double SED phenomenon appeared in the North American sector, which is the first of its kind to be reported. Further analysis showed that the temporal and spatial changes in the SEDs were associated with the eastward auroral electrojet.
Is the Gridded Data Accurate? Evaluation of Precipitation and Historical Wet and Dry Periods from ERA5 Data for Canadian Prairies
Authors: Frank Thiago , da Silva Junior Carlos Antonio , Chutko Krystopher J. , Teodoro Paulo Eduardo , de Oliveira-Júnior José Francisco , Guo Xulin
Published: December 2022

Precipitation is crucial for the hydrological cycle and is directly related to many ecological processes. Historically, measurements of precipitation totals were made at weather stations, but spatial and temporal coverage suffered due to the lack of a robust network of weather stations and temporal gaps in observations. Several products have been proposed to identify the location of the occurrence of precipitation and measure its intensity from different types of estimates, based on alternative data sources, that have global (or quasi-global) coverage with long historical time series. However, there are concerns about the accuracy of these estimates. The objective of this study is to evaluate the accuracy of the ERA5 product for two ecoregions of the Canadian Prairies through comparison with monthly means measured from 1981–2019 at ten weather stations (in-situ), as well as to assess the intraseasonal variability of precipitation and identify dry and wet periods based on the annual Standardized Precipitation Index (SPI) derived from ERA5. A significant relationship between in-situ data and ERA5 data (with the R2 varying between 0.42 and 0.76) (p < 0.01)) was observed in nine of the ten weather stations analyzed, with lower RMSE in the Mixed Ecoregion. The Mean Absolute Percentage Error (MAPE) results showed greater agreement between the datasets in May (average R value of 0.84 and an average MAPE value of 32.33%), while greater divergences were observed in February (average R value of 0.57 and an average MAPE value of 50.40%). The analysis of wet and dry periods, based on the SPI derived from ERA5, and the comparison with events associated with the El Niño-Southern Oscillation (ENSO), showed that from the ERA5 data and the derivation of the SPI it is possible to identify anomalies in temporal series with consistent patterns that can be associated with historical events that have been highlighted in the literature. Therefore, our results show that ERA5 data has potential to be an alternative for estimating precipitation in regions with few in-situ stations or with gaps in the time series in the Canadian Prairies, especially at the beginning of the growing season.
Compact Dual Circularly-Polarized Quad-Element MIMO/Diversity Antenna for Sub-6 GHz Communication Systems
Authors: Kumar Sachin , Palaniswamy Sandeep Kumar , Choi Hyun Chul , Kim Kang Wook
Published: December 2022

In this paper, a compact dual circularly-polarized (CP) planar multiple-input-multiple-output (MIMO) antenna is presented for a sub-6 GHz frequency band. The antenna consists of four identical resonating elements, which are placed in a mirrored-image pattern to obtain polarization diversity. Element 2 is a mirror image of element 1, and elements 3 and 4 are mirror images of elements 1 and 2. Each antenna element comprises an elliptical resonator, a 50-Ω microstrip feed line, and a rectangular stub integrated with the feed to increase the surface current path of the antenna, shifting the resonating frequency to the lower side. Additionally, the rectangular stub is lengthened towards the right side (along the +x-axis direction in the antenna element 1), which balances the magnitude and 90° phase variance among the horizontal (Ex) and vertical (Ey) fields. The proposed MIMO antenna supports both types of circular polarization, where radiators 1 and 3 radiate right-hand CP (RHCP) rays and radiators 2 and 4 radiate left-hand CP (LHCP) rays. Developing a compact-size MIMO antenna is a challenging task, especially when the antenna elements share the same ground plane and are placed less than half a wavelength apart. The mutual coupling in the proposed antenna is reduced by increasing the spacing between the elements without the use of any extra decoupling structure. Optimal spacing is maintained to achieve compact geometry with less inter-element correlation. The radiators are closely placed with an edge-to-edge spacing of 0.08λ0, where λ0 is the free space wavelength at 3.6 GHz. A peak gain of 5 dBi, efficiency of 90%, an envelope correlation coefficient (ECC) of less than 0.1, and isolation of more than 18 dB are obtained between different ports of the prototype antenna. The overall size of the antenna element is 17 mm × 17 mm × 1.6 mm, and the MIMO antenna is 40 mm × 40 mm × 1.6 mm.
EPSDNet: Efficient Campus Parking Space Detection via Convolutional Neural Networks and Vehicle Image Recognition for Intelligent Human–Computer Interactions
Authors: An Qing , Wang Haojun , Chen Xijiang
Published: December 2022

The parking problem, which is caused by a low parking space utilization ratio, has always plagued drivers. In this work, we proposed an intelligent detection method based on deep learning technology. First, we constructed a TensorFlow deep learning platform for detecting vehicles. Second, the optimal time interval for extracting video stream images was determined in accordance with the judgment time for finding a parking space and the length of time taken by a vehicle from arrival to departure. Finally, the parking space order and number were obtained in accordance with the data layering method and the TimSort algorithm, and parking space vacancy was judged via the indirect Monte Carlo method. To improve the detection accuracy between vehicles and parking spaces, the distance between the vehicles in the training dataset was greater than that of the vehicles observed during detection. A case study verified the reliability of the parking space order and number and the judgment of parking space vacancies.
Extended Energy-Expenditure Model in Soccer: Evaluating Player Performance in the Context of the Game
Authors: Skoki Arian , Rossi Alessio , Cintia Paolo , Pappalardo Luca , Štajduhar Ivan
Published: December 2022

Every soccer game influences each player’s performance differently. Many studies have tried to explain the influence of different parameters on the game; however, none went deeper into the core and examined it minute-by-minute. The goal of this study is to use data derived from GPS wearable devices to present a new framework for performance analysis. A player’s energy expenditure is analyzed using data analytics and K-means clustering of low-, middle-, and high-intensity periods distributed in 1 min segments. Our framework exhibits a higher explanatory power compared to usual game metrics (e.g., high-speed running and sprinting), explaining 45.91% of the coefficient of variation vs. 21.32% for high-, 30.66% vs. 16.82% for middle-, and 24.41% vs. 19.12% for low-intensity periods. The proposed methods enable deeper game analysis, which can help strength and conditioning coaches and managers in gaining better insights into the players’ responses to various game situations.
Disentangling Noise from Images: A Flow-Based Image Denoising Neural Network
Authors: Liu Yang , Anwar Saeed , Qin Zhenyue , Ji Pan , Caldwell Sabrina , Gedeon Tom
Published: December 2022

The prevalent convolutional neural network (CNN)-based image denoising methods extract features of images to restore the clean ground truth, achieving high denoising accuracy. However, these methods may ignore the underlying distribution of clean images, inducing distortions or artifacts in denoising results. This paper proposes a new perspective to treat image denoising as a distribution learning and disentangling task. Since the noisy image distribution can be viewed as a joint distribution of clean images and noise, the denoised images can be obtained via manipulating the latent representations to the clean counterpart. This paper also provides a distribution-learning-based denoising framework. Following this framework, we present an invertible denoising network, FDN, without any assumptions on either clean or noise distributions, as well as a distribution disentanglement method. FDN learns the distribution of noisy images, which is different from the previous CNN-based discriminative mapping. Experimental results demonstrate FDN’s capacity to remove synthetic additive white Gaussian noise (AWGN) on both category-specific and remote sensing images. Furthermore, the performance of FDN surpasses that of previously published methods in real image denoising with fewer parameters and faster speed.
Person Re-Identification with Improved Performance by Incorporating Focal Tversky Loss in AGW Baseline
Authors: Huang Shao-Kang , Hsu Chen-Chien , Wang Wei-Yen
Published: December 2022

Person re-identification (re-ID) is one of the essential tasks for modern visual intelligent systems to identify a person from images or videos captured at different times, viewpoints, and spatial positions. In fact, it is easy to make an incorrect estimate for person re-ID in the presence of illumination change, low resolution, and pose differences. To provide a robust and accurate prediction, machine learning techniques are extensively used nowadays. However, learning-based approaches often face difficulties in data imbalance and distinguishing a person from others having strong appearance similarity. To improve the overall re-ID performance, false positives and false negatives should be part of the integral factors in the design of the loss function. In this work, we refine the well-known AGW baseline by incorporating a focal Tversky loss to address the data imbalance issue and facilitate the model to learn effectively from the hard examples. Experimental results show that the proposed re-ID method reaches rank-1 accuracy of 96.2% (with mAP: 94.5) and rank-1 accuracy of 93% (with mAP: 91.4) on Market1501 and DukeMTMC datasets, respectively, outperforming the state-of-the-art approaches.
Data Integration from Heterogeneous Control Levels for the Purposes of Analysis within Industry 4.0 Concept
Authors: Horak Tibor , Strelec Peter , Kebisek Michal , Tanuska Pavol , Vaclavova Andrea
Published: December 2022

Small- and medium-sized manufacturing companies must adapt their production processes more quickly. The speed with which enterprises can apply a change in the context of data integration and historicization affects their business. This article presents the possibilities of implementing the integration of control processes using modern technologies that will enable the adaptation of production lines. Integration using an object-oriented approach is suitable for complex tasks. Another approach is data integration using the entity referred to as tagging (TAG). Tagging is essential to apply for fast adaptation and modification of the production process. The advantage is identification, easier modification, and generation of data structures where basic entities include attributes, topics, personalization, locale, and APIs. This research proposes a model for integrating manufacturing enterprise data from heterogeneous levels of management. As a result, the model and the design procedure for data integrating production lines can efficiently adapt production changes.
Towards a Practical Implementation of a Single-Beam All-Optical Non-Zero-Field Magnetic Sensor for Magnetoencephalographic Complexes
Authors: Petrenko Mikhail , Vershovskii Anton
Published: December 2022

We present a single-beam all-optical two-channel magnetic sensor scheme developed for biological applications such as non-zero-field magnetoencephalography and magnetocardiography. The pumping, excitation and detection of magnetic resonance in two cells are performed using a single laser beam with time-modulated linear polarization: the linear polarization of the beam switches to orthogonal every half-cycle of the Larmor frequency. Light with such characteristics can be transmitted over a single-mode polarization-maintaining fiber without any loss in the quality of the polarization characteristics. We also present an algorithm for calculating optical elements in a sensor scheme, the results of measuring the parametric dependences of magnetic resonance in cells, and the results of direct testing of a sensor in a magnetic shield. We demonstrate sensitivity at the level of 20 fT/√Hz in one sensor channel in the frequency range of 80–200 Hz.
Application for Recognizing Sign Language Gestures Based on an Artificial Neural Network
Authors: Kozyra Kamil , Trzyniec Karolina , Popardowski Ernest , Stachurska Maria
Published: December 2022

This paper presents the development and implementation of an application that recognizes American Sign Language signs with the use of deep learning algorithms based on convolutional neural network architectures. The project implementation includes the development of a training set, the preparation of a module that converts photos to a form readable by the artificial neural network, the selection of the appropriate neural network architecture and the development of the model. The neural network undergoes a learning process, and its results are verified accordingly. An internet application that allows recognition of sign language based on a sign from any photo taken by the user is implemented, and its results are analyzed. The network effectiveness ratio reaches 99% for the training set. Nevertheless, conclusions and recommendations are formulated to improve the operation of the application.
A Comparative Study on a Novel Quality Assessment Protocol Based on Image Analysis Methods for Color Doppler Ultrasound Diagnostic Systems
Authors: Fiori Giorgia , Pica Andrada , Sciuto Salvatore Andrea , Marinozzi Franco , Bini Fabiano , Scorza Andrea
Published: December 2022

Color Doppler (CD) imaging is widely used in diagnostics since it allows real-time detection and display of blood flow superimposed on the B-mode image. Nevertheless, to date, a shared worldwide standard on Doppler equipment testing is still lacking. In this context, the study herein proposed would give a contribution focusing on the combination of five test parameters to be included in a novel Quality Assessment (QA) protocol for CD systems testing. A first approach involving the use of the Kiviat diagram was investigated, assuming the diagram area, normalized with respect to one of the gold standards, as an index of the overall Doppler system performance. The QA parameters were obtained from the post-processing of CD data through the implementation of custom-written image analysis methods and procedures, here applied to three brand-new high-technology-level ultrasound systems. Experimental data were collected through phased and convex array probes, in two configuration settings, by means of a Doppler flow phantom set at different flow rate regimes. The outcomes confirmed that the Kiviat diagram might be a promising tool applied to quality controls of Doppler equipment, although further investigations should be performed to assess the sensitivity and specificity of the proposed approach.
Objective Evaluation of the Somatogravic Illusion from Flight Data of an Airplane Accident
Authors: Groen Eric L. , Clark Torin K. , Houben Mark M. J. , Bos Jelte E. , Mumaw Randall J.
Published: December 2022

(1) Background: It is difficult for accident investigators to objectively determine whether spatial disorientation may have contributed to a fatal airplane accident. In this paper, we evaluate three methods to reconstruct the possible occurrence of the somatogravic illusion based on flight data recordings from an airplane accident. (2) Methods: The outputs of two vestibular models were compared with the “standard” method, which uses the unprocessed gravito-inertial acceleration (GIA). (3) Results: All three methods predicted that the changing orientation of the GIA would lead to a somatogravic illusion when no visual references were available. However, the methods were not able to explain the first pitch-down control input by the pilot flying, which may have been triggered by the inadvertent activation of the go-around mode and a corresponding pitch-up moment. Both vestibular models predicted a few seconds delay in the illusory tilt from GIA due to central processing and sensory integration. (4) Conclusions: While it is difficult to determine which method best predicted the somatogravic illusion perceived during the accident without data on the pilot’s pitch perception, both vestibular models go beyond the GIA analysis in taking into account validated vestibular dynamics, and they also account for other vestibular illusions. In that respect, accident investigators would benefit from a unified and validated vestibular model to better explain pilot actions in accidents related to spatial disorientation.
Corporate Social Responsibility on Twitter: A Review of Topics and Digital Communication Strategies’ Success Factors
Authors: Pilgrim Katharina , Bohnet-Joschko Sabine
Published: December 2022

Corporate social responsibility (CSR) has become increasingly important for companies in recent years. On the one hand, regulatory frameworks require the disclosure of measures for sustainable management. On the other hand, for long-term corporate success, stakeholders must be strategically engaged in the dialog on sustainability aspects. Social media and Twitter in particular offer the potential to foster a meaningful stakeholder dialogue on CSR topics. Twitter’s strategic realignment due to Elon Musk’s acquisition in the fall of 2022, provides an opportunity to capture research results on activities and strategies on the platform systematically, and to synthesize information for future comparative longitudinal studies of changes in usage. We conducted a literature review including 42 papers to contribute to the body of evidence on CSR communication strategies on Twitter across industries and countries, by deriving interdisciplinary suggestions for strategic CSR-related stakeholder management. Results cover relevant CSR topics, prioritized stakeholder groups for CSR communication on Twitter, and successful communication strategies for companies to obtain beneficial results, such as generating social media capital. The results contribute to the strategic planning and implementation of CSR stakeholder management on Twitter, and offer starting points for future studies on social-media mining and CSR communication strategies.
Factors Affecting Environmental Pollution for Sustainable Development Goals—Evidence from Asian Countries
Authors: Thu Nguyen Thi Phuong , Huong Le Mai , Xuan Vu Ngoc
Published: December 2022

The world is faced with climate change and gradual increases in seawater and carbon dioxide levels, and leaders of countries all over the world need to take action in order to achieve the Sustainable Development Goals (SDGs). This paper aims to identify the factors affecting environmental pollution in Asian countries for sustainable development. This study collected data from the World Bank covering 2000–2020 for 15 Asian countries. The data were processed via STATA 17.0; the study employed the unrestricted fixed effect to solve the research problems. The empirical results suggest that electricity consumption, fossil fuel consumption, renewable consumption, population, imports, and exports affected environmental pollution in the 15 Asian countries. In addition, electricity consumption and fossil fuel consumption had a strong positive effect on Asia’s environmental pollution. Moreover, population and renewable consumption negatively affected CO2 emissions. These results indicate that, if an Asian country’s electricity consumption increases by 1%, then its CO2 emissions will increase by 0.674%; if an Asian country’s fossil fuel consumption increases by 1%, then its CO2 emissions will increase by 0.203%; if an Asian country’s renewable consumption increases by 1%, then its CO2 emissions will decrease by 0.01568%; if an Asian country’s export of goods and services increases by 1%, then its CO2 emissions will decrease by 0.054%; if an Asian country’s import of goods and services increases by 1%, then its CO2 emissions will increase by 0.067%; if an Asian country’s population increases by 1%, then its CO2 emissions will decrease by 0.2586%. Based on the empirical results, the study suggests new policies for green energy to achieve the Sustainable Development Goals (SDGs).
Allocation of Resources for Emergency Response to Coal-to-Oil Hazardous Chemical Accidents under Railway Transportation Mode
Authors: Zhao Kaigong , Zhang Xiaolei , Wang Hui , Gai Yongling , Wang Haiyan
Published: December 2022

Railways of the National Energy Group using their own trains have become an important mode of transportation for coal-to-oil hazardous chemicals. Under the circumstances of the shortage of emergency resources and the coupling of multiple disasters, how to establish an effective and reasonable emergency resource allocation scheme for the railway transportation of dangerous chemicals from a disaster site is of great significance to the national task of ensuring safety for the transportation of energy. This paper focuses on the allocation of emergency rescue resources for railway transportation accidents involving coal-to-oil hazardous chemicals, considering the scenarios of the leakage of coal-to-oil, railway line damage, etc. According to the number of trapped people at the initial moment, the disaster situation and accident type, affected areas, etc., a multi-objective optimization model with the shortest response time of the emergency team and the lowest cost of transporting emergency materials along the railway transportation channel of coal-to-oil hazardous chemicals is constructed, based on the calculation method using the initial weight and the emergency weight assigned by the emergency rescue team. Furthermore, in order to avoid the problem of the weight of the local accident points being too small to participate in a rescue, a bee colony algorithm model based on pre-allocation was designed and compared with two traditional algorithms, allowing the realization of the search and selection of allocation methods. The analysis of the examples shows that the proposed method is efficient and fast, and the research results are practical and feasible, which can provide a scientific basis for the rapid decision of emergency rescue resource allocation in multi-disaster scenarios for large energy groups, and provide a reference for the allocation of public security emergency resources in the national emergency response.
Cost Sharing in Insurance Communities: A Hybrid Approach Based on Multiple-Choice Objective Programming and Cooperative Games
Authors: Li Yuanzhong , Cao Xinbang , Qu Shaojian , Ji Ying , Xia Zilong
Published: December 2022

At present, utilizing the insurance community is a common method to deal with investment risks along the Belt and Road; however, there is no clear method or mechanism to deal with the decision-making optimization and cost allocation of the insurance community participants. We propose a hybrid approach to solve this problem. First, we construct an underwriting decision optimization model for the insurance community using the multi-choice goal programming method, which generates the cost characteristic function based on a cooperative alliance. Second, we use the cooperative game method combined with the modified Shapley value method to take risk factors into consideration, which allows us to optimize the cost allocation among members of the insurance community. Finally, our simulation analysis results show that the multi-choice goal programming method can optimize the insurance community’s underwriting decisions. Specifically, the total underwriting cost is lower than the sum of the underwriting costs under the insurance company’s single-action strategy, and the total underwriting scale is as large as possible. Compared with the classical Shapley value method, the modified Shapley value method can better reflect differences in the underwriting risks of different regions, encouraging governments to take measures to reduce underwriting risks. To conclude, we propose some suggestions based on our research findings. The possible contributions of this paper are as follows: our research provides a hybrid optimization method based on multiple-choice objective programming and cooperative games to solve the cost allocation problem facing the insurance community, and it has some reference value for improving the cost-sharing system of the insurance community.
A Biography of an Ancient Cultural Landscape: The Sky over Tarquinia
Authors: Bagnasco Gianni Giovanna , Garzulino Andrea , Marzullo Matilde , Pernigotti Antonio Paolo
Published: December 2022

This paper discusses two kinds of research implemented to federate different disciplines and knowledge in support of archaeological research and the protection of the tangible and intangible heritage of ancient Tarquinia. The first part of the work examines the results obtained from the archaeological analysis, the concrete implications on the sustainability of ancient cultural landscapes and their possible transmission over time as an expression of the culture of a community. The second part of the work presents the reading and analysis of the ancient landscape and sites through chrono-stratigraphy, especially regarding two case studies in Tarquinia: the ‘monumental complex’ and the Ara della Regina sanctuary. The work focuses on the intangible aspects of the landscape as a result of archaeological research in the archaeoastronomical field. The orientation of the sacred structures and landscapes is presented herein regarding Etruria and the two case studies. The results shed light on the city’s perception by the population, identifying it as an entity that held and sheltered every aspect of the community’s life. The preliminary results of this study have made it possible to recognise aspects of significant historical and cultural value, which are the heterogeneous expression of a solid identity to be safeguarded and developed in a sustainable way.
The Impact of COVID-19 on Ethnic Business Households Involved in Tourism in Ninh Thuan, Vietnam
Authors: Wu Chihkang Kenny , Nguyen Ngoc Anh , Dang Thanh Quoc Thuan , Nguyen Mai-Uyen
Published: December 2022

Since the COVID-19 outbreak at the end of 2019, there have been many studies on its impact on the tourism industry. However, research on the effects of this pandemic on ethnic tourism business households is minimal. This study explores how COVID-19 has affected ethnic minority tourism businesses and how they have responded to the crisis. Two ancient craft villages of the Cham people, which are popular destinations in Ninh Thuan province, were selected as case studies. Data were collected from late 2021 to early 2022 through fieldwork and in-depth interviews with 20 subjects who ran Cham-owned business households. A mini-survey of 52 Cham-owned tourism business households was also conducted as a qualitative method to supplement the statistical data. The findings of this study are: the Cham tourism business households have been affected by the COVID-19 pandemic, but not significantly; and that the Cham business households have utilized their own advantages (such as a small business scale, utilization of available advantages, reasonable gender division of labor in the family, changing business strategies, and taking advantage of social media) to weather the crisis. This article contributes to the literature on the impact of disasters on tourism by focusing on how ethnic minorities use the business household model to overcome a crisis and by presenting evidence that ethnic tourism combined with business households is a sustainable model.
A Multi-Criteria Decision-Making Framework for Sustainable Supplier Selection in the Circular Economy and Industry 4.0 Era
Authors: Xie Ziyuan , Tian Guixian , Tao Yongchao
Published: December 2022

Supplier selection is a difficult and important issue in sustainable supply chain management. This research proposes a managerial framework based on Industry 4.0, a plan for evaluating and choosing sustainable suppliers to implement circular economy practices. Green supplier selection (GSS), the circular economy, and Industry 4.0 have become hot topics in recent operations management discussions. Three main categories (e.g., economic, environmental, and social) and 16 subcategories related to supplier selection decisions were identified using a hybrid approach combining literature reviews and industry expert opinions. In the fuzzy environment of Pythagorean, this paper proposes comprehensive techniques for the selection of green suppliers based on entropy, stepwise weighted assessment ratio analysis (SWARA), and complex proportional assessment (COPRAS) methods. To calculate the standard weight, this technique first merges the objective weight found by the entropy method and the subjective weight found by the SWARA method. The findings show that access to finance and financial availability for implementing Industry 4.0 within the circular economy (ECO5) and R&D in environmental issues using Industry 4.0 technologies (ENV7), Information technology (IT) facilities (ECO6), and Product cost/price (ECO1) showed highest ranking among sub-criteria. Moreover, Supplier 5 was listed as the best sustainable supplier when they started making such a decision. The results of the proposed method help decision-makers make effective and efficient sustainable supplier selection.