bluuebunny/crossref_metadata_2025 huggingface dataset:
LL-37-Coupled Porous Composite Scaffold for the Treatment of Infected Segmental Bone Defect
Authors: Li Xialin , Huang Xingyu , Li Long , Wu Jiayi , Yi Weihong , Lai Yuxiao , Qin Lei
Published: December 2022

Increased multiantibiotic-resistant bacteria means that infected bone defects remain a significant challenge to clinics. Great interest has emerged in the use of non-antibiotic antimicrobials to reduce the rate of multiantibiotic-resistant bacterial infection and facilitate bone regeneration. The cationic antimicrobial peptide LL-37 is the sole human cathelicidin and has shown nonspecific activity against a broad spectrum of microorganisms. In this study, we fabricated the poly(lactic-co-glycolic acid)/β-calcium phosphate/peptide LL-37 (PLGA/TCP/LL-37, PTL) scaffold with low-temperature 3D-printing technology for the treatment of infected segmental bone defects. The prepared scaffolds were divided into three groups: a high LL-37 concentration group (PTHL), low LL-37 concentration group (PTLL) and blank control group (PT). The cytocompatibility and antimicrobial activity of the engineered scaffolds were tested in vitro, and their osteogenesis properties were assessed in vivo in a rat infected bone defect model. We found the fabricated PTL scaffold had a well-designed porous structure that could support a steady and prolonged LL-37 release. Furthermore, the PTHL group showed strong antibacterial activity against Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli) without any inhibition of the proliferation or alkaline phosphatase activity of rat bone marrow mesenchymal stem cells (BMSCs) in vitro. In addition, the infected femoral defects implanted with PTHL group displayed new bone formation in four weeks without any evidence of residual bacteria, which showed similar antibacterial outcomes to the vancomycin and cancellous bone mixture group. In conclusion, the PTHL composite scaffold is a promising non-antibiotic antimicrobial graft with good biodegradability, biocompatibility, and osteogenic capability for infected bone defects.
A Supramolecular Nanoassembly of Lenvatinib and a Green Light-Activatable NO Releaser for Combined Chemo-Phototherapy
Authors: Laneri Francesca , Licciardello Nadia , Suzuki Yota , Graziano Adriana C. E. , Sodano Federica , Fraix Aurore , Sortino Salvatore
Published: December 2022

The chemotherapeutic Lenvatinib (LVB) and a nitric oxide (NO) photodonor based on a rhodamine antenna (RD-NO) activatable by the highly compatible green light are supramolecularly assembled by a β-cyclodextrin branched polymer (PolyCD). The poorly water-soluble LVB and RD-NO solubilize very well within the polymeric host leading to a ternary supramolecular nanoassembly with a diameter of ~55 nm. The efficiency of the NO photorelease and the typical red fluorescence of RD-NO significantly enhance within the polymer due to its active role in the photochemical and photophysical deactivation pathways. The co-presence of LVB within the same host does not affect either the nature or the efficiency of the photoinduced processes of RD-NO. Besides, irradiation of RD-NO does not lead to the decomposition of LVB, ruling out any intermolecular photoinduced process between the two guests despite sharing the same host. Ad-hoc devised Förster Resonance Energy Transfer experiments demonstrate this to be the result of the not close proximity of the two guests, which are confined in different compartments of the same polymeric host. The supramolecular complex is stable in a culture medium, and its biological activity has been evaluated against HEP-G2 hepatocarcinoma cell lines in the dark and under irradiation with visible green light, using LVB at a concentration well below the IC50. Comparative experiments performed using the polymeric host encapsulating the individual LVB and RD-NO components under the same experimental conditions show that the moderate cell mortality induced by the ternary complex in the dark increases significantly upon irradiation with visible green light, more likely as the result of synergism between the NO photogenerated and the chemotherapeutic.
The “Light Knife” for Gastric Cancer: Photodynamic Therapy
Authors: Wang Haiyun , Ewetse Maswikiti Paul , Ma Chenhui , Pu Weigao , Xu Bo , He Puyi , Wang Yunpeng , Zhu Jingyu , Chen Hao
Published: December 2022

Photodynamic therapy (PDT) has been used clinically to treat cancer for more than 40 years. Some solid tumors, including esophageal cancer, lung cancer, head and neck cancer, cholangiocarcinoma, and bladder cancer, have been approved for and managed with PDT in many countries globally. Notably, PDT for gastric cancer (GC) has been reported less and is not currently included in the clinical diagnosis and treatment guidelines. However, PDT is a potential new therapeutic modality used for the management of GC, and its outcomes and realization are more and more encouraging. PDT has a pernicious effect on tumors at the irradiation site and can play a role in rapid tumor shrinkage when GC is combined with cardiac and pyloric obstruction. Furthermore, because of its ability to activate the immune system, it still has a specific effect on systemic metastatic lesions, and the adverse reactions are mild. In this Review, we provide an overview of the current application progress of PDT for GC; systematically elaborate on its principle, mechanism, and the application of a new photosensitizer in GC; and focus on the efficacy of PDT in GC and the prospect of combined use with other therapeutic methods to provide a theoretical basis for clinical application.
Diclofenac Loaded Biodegradable Nanoparticles as Antitumoral and Antiangiogenic Therapy
Authors: Esteruelas Gerard , Souto Eliana B. , Espina Marta , García María Luisa , Świtalska Marta , Wietrzyk Joanna , Gliszczyńska Anna , Sánchez-López Elena
Published: December 2022

Cancer is identified as one of the main causes of death worldwide, and an effective treatment that can reduce/eliminate serious adverse effects is still an unmet medical need. Diclofenac, a non-steroidal anti-inflammatory drug (NSAID), has demonstrated promising antitumoral properties. However, the prolonged use of this NSAID poses several adverse effects. These can be overcome by the use of suitable delivery systems that are able to provide a controlled delivery of the payload. In this study, Diclofenac was incorporated into biodegradable polymeric nanoparticles based on PLGA and the formulation was optimized using a factorial design approach. A monodisperse nanoparticle population was obtained with a mean size of ca. 150 nm and negative surface charge. The release profile of diclofenac from the optimal formulation followed a prolonged release kinetics. Diclofenac nanoparticles demonstrated antitumoral and antiangiogenic properties without causing cytotoxicity to non-tumoral cells, and can be pointed out as a safe, promising and innovative nanoparticle-based formulation with potential antitumoral effects.
Direct Synthesis of Partially Chain-Straightened Propylene Oligomers and P-MA Co-Oligomers Using Axially Flexible Shielded Iminopyridyl Palladium Complexes
Authors: Sun Huayin , Fan Huijun , Zhu Chuangao , Zou Wenping , Dai Shengyu
Published: December 2022

In this study, a series of partially chain-straightened propylene oligomers and functional propylene–methyl acrylate (P-MA) co-oligomers were synthesized with 8-alkyl-iminopyridyl Pd(II) catalysts. The molecular weight and polar monomer incorporation ratio could be tuned by using Pd(II) catalysts with various 8-alkyl-naphthyl substituents (8-alkyl: H, Me, and n-Bu). In propylene oligomerization, all the 8-alkyl-iminopyridyl Pd(II) catalysts convert propylene to partially chain-straightened (119–136/1000 C) oligomers with low molecular weights (0.3–1.5 kg/mol). Among the catalysts, Pd1 with non-substituent (H) on the ligand showed the highest activity of 5.4 × 104 g/((mol of Pd) h), generating oligomers with the lowest molecular weight (Mn: 0.3 kg/mol). Moreover, polar-functionalized propylene-MA co-oligomers with very high incorporation ratios (22.8–36.5 mol %) could be obtained in the copolymerization using these 8-alkyl-iminopyridyl Pd(II) catalysts. Additionally, Pd1 exhibited the best performance in propylene-MA copolymerization as it displayed the highest MA incorporation ratio of up to 36.5 mol%. All the three catalysts are capable of generating partially chain-straightened P-MA co-oligomers and the activities decrease gradually while the molecular weight increases with the increasing steric hindrance of the alkyl substituent (H < Me < n-Bu). Compared to Pd4 with the rigid 8-aryl substituent, the flexible 8-alkyl-iminopyridyl Pd(II) catalysts (Pd1-3) not only showed much higher activities in the propylene oligomerization, but also yielded P-MA co-oligomers with significantly higher incorporation ratios in the propylene co-oligomerization.
Nano Ag/Co3O4 Catalyzed Rapid Decomposition of Robinia pseudoacacia Bark for Production Biofuels and Biochemicals
Authors: Yue Xiaochen , Chen Xiangmeng , Li Hanyin , Ge Shengbo , Yang Yafeng , Peng Wanxi
Published: December 2022

Biomass energy has attracted widespread attention due to its renewable, storage, huge production and clean and pollution-free advantages. Using Robinia pseudoacacia bark (RPB) as raw material, biogas and bio-oil produced by pyrolysis of RPB were detected and analyzed by TG-DTG, TG-FTIR and PY-GC-MS under the action of nanocatalysis. TG results showed that CH4 and CO flammable gases were produced by pyrolysis. PY-GC-MS results showed that RPB was rapidly pyrolyzed to obtain alcohols, ketones, aldehydes and acids bio-oil. The content of phenolic substances was the highest, accounting for 32.18% of all substances.Nanocatalysis has a certain effect on RPB, accelerating the precipitation of pyrolysis products and improving the over-oxidation of bio-oil. In addition, the extracts of RPB were identified and analyzed by FTIR, NMR, GC-MS and LC-Q-TOF-MS, and more than 100 active ingredients, such as Betaine, Epicathin and β-sitosterol, were detected. Their applications as additive energy in other fields were explored. Therefore, Robinia pseudoacacia bark constitutes a fine biofeedstock for biofuels and biochemicals.
Silver Nanoparticles Loaded on Polyethylene Terephthalate Films Grafted with Chitosan
Authors: Flores-Rojas Guadalupe Gabriel , López-Saucedo Felipe , Vera-Graziano Ricardo , Magaña Héctor , Mendizábal Eduardo , Bucio Emilio
Published: December 2022

Currently, polyethylene terephthalate (PET) is one of the most widely used polymeric materials in different sectors such as medicine, engineering, and food, among others, due to its benefits, including biocompatibility, mechanical resistance, and tolerance to chemicals and/or abrasion. However, despite all these excellent characteristics, it is not capable of preventing the proliferation of microorganisms on its surface. Therefore, providing this property to PET remains a difficult challenge. Fortunately, different strategies can be applied to remove microorganisms from the PET surface. In this work, the surface of the PET film was functionalized with amino groups and later with a dicarboxylic acid, allowing a grafting reaction with chitosan chains. Finally, the chitosan coating was loaded with silver nanoparticles with an average size of 130 ± 37 nm, presenting these materials with an average cell viability of 80%. The characterization of these new PET-based materials showed considerable changes in surface morphology as well as increased surface hydrophilicity without significantly affecting their mechanical properties. In general, the implemented method can open an alternative pathway to design new PET-based materials due to its good cell viability with possible bacteriostatic activity due to the biocidal properties of silver nanoparticles and chitosan.
The Long-Term Mechanical Properties of BS Perpendicular to the Grain
Authors: Luo Xiangya , Luo Xiangqian , Ren Haiqing , Zhang Shuangbao , Zhong Yong
Published: December 2022

As a modern bamboo composite with good mechanical properties, bamboo scrimber (BS) has achieved prominence in the sustainable architecture field. When used as a structural material, it is inevitably under continual tension perpendicular to the grain, therefore its mechanical response under long-term loading is significant for structural design. In this study, tensile tests were conducted on BS under short-term and long-term loads perpendicular to the grain. The duration of load (DOL) effect on BS perpendicular to grain and its creep effect were analyzed. Compared with BS parallel to the grain, the DOL effect on BS perpendicular to the grain was less severe, and the capacity for creep resistance was weaker. The threshold stress ratio and relative creep strain of BS perpendicular to the grain were 0.40 and 0.87, respectively. It was found that the DOL models and the viscoelastic model accurately predicted the DOL factor and creep strain. This study provides a scientific reference for the safe lifetime service of BS in practical engineering.
The Journey to G.R.A.C.E: Creating an International Community of Practice
Authors: Robinson Christine , Cranley Linda , O’Connell Daniel
Published: December 2022

Global Researchers Advancing Catholic Education (G.R.A.C.E) is a unique Community of Practice (CoP). The CoP methodology was applied within G.R.A.C.E for its capacity to connect multi-disciplinary and international academics and practitioners within Catholic Education. This paper presents key insights gathered from the G.R.A.C.E steering committee regarding their perspectives on the journey of initiating this unique CoP. A small qualitative research project framed within a phenomenological interpretivist theoretical perspective was employed to ascertain the participants’ hopes, experiences, impact as well as challenges and opportunities. A Qualtrics questionnaire was the selected data collection method. Findings suggest that the experience of G.R.A.C.E has been a positive one, affirming the CoP methodology adopted was effective in ensuring the hopes that members held for the CoP were actualised. Challenges and opportunities identified in the findings provide insight into the future direction of this truly global initiative.
Israel and the Apostolic Mission: A Post-Supersessionist Reading of Ephesians and Colossians
Authors: Windsor Lionel J.
Published: December 2022

Interpretation of Ephesians and Colossians has often proceeded on the basis that the stance of the original authors and recipients towards Israel is supersessionist, i.e., that the church has entirely replaced or superseded Israel as the locus of divine scriptural promises. By contrast, this article presents a post-supersessionist reading of Ephesians and Colossians. The reading strategy seeks to read the letters as situated within the dynamics of the apostolic mission to proclaim the gospel of Jesus as the Jewish christos/messiah to the nations. This mission is envisaged in Acts as a priestly dynamic in which the blessings of salvation in the christos/messiah began within a distinctly Israelite original community and proceeded to the nations without necessarily negating Jewish distinctiveness. The reading highlights key instances of this Israel-centered missionary dynamic in Ephesians and Colossians. It also seeks to demonstrate how this dynamic helps to provide satisfactory answers to key exegetical questions in the letters. Furthermore, it offers alternative non-supersessionist readings of critical passages concerning circumcision, law, and Jewish identity in the two letters. The article is a distillation and summary of research in the author’s previously published book Reading Ephesians and Colossians After Supersessionism: Christ’s Mission through Israel to the Nations.
The Hard Road to Reform: Curriculum Renewal for Muslim Education in Early Twentieth-Century China
Authors: Liu Xunqian , Yang Yi
Published: December 2022

Since the early twentieth century, Chinese Muslim elites have been engaged in a movement aimed at developing a new style of education for Muslim children. These Muslim elites traveled to the Middle East and were influenced by the modernizing movement in the broader Islamic world. The new-style schools were no longer attached to mosques, and their curricula emphasized the inclusion of modern secular subjects. Islamic knowledge and disciplines began to be transmitted as modern subjects when taught in modern institutions. Based on the detailed analysis of historical documents, this paper examines the trajectories of several prominent modern institutions in Beijing to illustrate the key aspects of Muslim educational reform. The Muslim elites in charge of this educational reform share the common goals of promoting education and improved livelihoods for the urban Hui Muslims; to date, however, these goals have been only partially met, and a mismatch has emerged between the new knowledge that students have learned and the occupational composition of the Hui people in Niujie (mainly small traders).
A Catholic Pope and a Rawlsian Statesman: War and Peace through the Lens of Non-Public and Public Reason
Authors: Jose Jeff Shawn
Published: December 2022

A Catholic pope and a Rawlsian statesman respectively represent religious and political leaders who confront the reality of war and face the challenge of responding to it. A political decision during conflict based exclusively on religious or secular justifications will be unconvincing in a contemporary plural public space. John Rawls’s solution to this dilemma was to offer justifications based on public reason grounded on political values and not on religious or secular values that support non-public reason. However, restraining religious arguments can ignite passionate religious objections when the decisions of government contradict the demands of their religious values. Hence, this paper argues against an exclusive position and highlights the importance of a nuanced approach that engages religious and political perspectives. The arguments are presented by engaging both Catholic and Rawlsian responses to war by focusing on just war theory and the role of a statesman.
DCFusion: Dual-Headed Fusion Strategy and Contextual Information Awareness for Infrared and Visible Remote Sensing Image
Authors: Pu Qin , Chehri Abdellah , Jeon Gwanggil , Zhang Lei , Yang Xiaomin
Published: December 2022

In remote sensing, the fusion of infrared and visible images is one of the common means of data processing. Its aim is to synthesize one fused image with abundant common and differential information from the source images. At present, the fusion methods based on deep learning are widely employed in this work. However, the existing fusion network with deep learning fails to effectively integrate common and differential information for source images. To alleviate the problem, we propose a dual-head fusion strategy and contextual information awareness fusion network (DCFusion) to preserve more meaningful information from source images. Firstly, we extract multi-scale features for the source images with multiple convolution and pooling layers. Then, we propose a dual-headed fusion strategy (DHFS) to fuse different modal features from the encoder. The DHFS can effectively preserve common and differential information for different modal features. Finally, we propose a contextual information awareness module (CIAM) to reconstruct the fused image. The CIAM can adequately exchange information from different scale features and improve fusion performance. Furthermore, the whole network was tested on MSRS and TNO datasets. The results of extensive experiments prove that our proposed network achieves good performance in target maintenance and texture preservation for fusion images.
Improve the Accuracy in Numerical Modeling of Suspended Sediment Concentrations in the Hangzhou Bay by Assimilating Remote Sensing Data Utilizing Combined Techniques of Adjoint Data Assimilation and the Penalty Function Method
Authors: Chen Wenrui , Wang Daosheng , Liu Xiujuan , Cheng Jun , Zhang Jicai
Published: December 2022

Suspended sediment dynamics play an important role in controlling nearshore and estuarine geomorphology and the associated ecological environments. Modeling the transport of suspended sediment is a complicated and challenging research topic. The goal of this study is to improve the accuracy of modeling the suspended sediment concentrations (SSCs) with newly developed techniques. Based on a three-dimensional suspended cohesive sediment transport model, the transport of suspended sediment and SSCs are simulated by assimilating SSCs retrieved from the Geostationary Ocean Color Imager (GOCI) with the adjoint data assimilation in the Hangzhou Bay, a typical strong tidal estuary along the coast of the East China Sea. To improve the effect of the data assimilation, the penalty function method, in which the reasonable constraints of the estimated model parameters are added to the cost function as penalty terms, will be introduced for the first time into the adjoint data assimilation in the SSCs modeling. In twin experiments, the prescribed spatially varying settling velocity is estimated by assimilating the synthetic SSC observations, and the results show that the penalty function method can further improve the effect of data assimilation and parameter estimation, regardless of synthetic SSC observations being contaminated by random artificial errors. In practical experiments, the spatially varying settling velocity is firstly estimated by assimilating the actual GOCI-retrieved SSCs. The results demonstrate that the simulated results can be improved by the adjoint data assimilation, and the penalty function method can additionally reduce the mean absolute error (MAE) between the independent check observations and the corresponding simulated SSCs from 1.44 × 10−1 kg/m3 to 1.30 × 10−1 kg/m3. To pursue greater simulation accuracy, the spatially varying settling velocity, resuspension rate, critical shear stress and initial conditions are simultaneously estimated by assimilating the actual GOCI-retrieved SSCs to simulate the SSCs in the Hangzhou Bay. When the adjoint data assimilation and the penalty function method are simultaneously used, the MAE between the independent check observations and the corresponding simulated SSCs is just 9.90 × 10−2 kg/m3, which is substantially less than that when only the settling velocity is estimated. The MAE is also considerably less than that when the four model parameters are estimated to be without using the penalty function method. This study indicates that the adjoint data assimilation can effectively improve the SSC simulation accuracy, and the penalty function method can limit the variation range of the estimated model parameters to further improve the effect of data assimilation and parameter estimation.
Dynamic Monitoring of Debris-Covered Glacier Surface Velocity and Ice Thickness of Mt.Tomur, Tian Shan, China
Authors: Bai Changbin , Wang Feiteng , Wang Lin , Xu Chunhai , Yue Xiaoying , Yang Shujing , Wang Puyu , Bi Yanqun , Wei Haining
Published: December 2022

The Mt.Tomur glaciers, in the Tian Shan mountains of Western China, are usually debris-covered, and due to climate change, glacial hazards are becoming more frequent in this region. However, no changes in the long-time series of glacier surface velocities have been observed in this region. Conducting field measurements in high-altitude mountains is relatively difficult, and consequently, the dynamics and driving factors are less studied. Here, image-correlation offset tracking using Landsat images was exploited to estimate the glacier surface velocity of glaciers in the Mt.Tomur region from 2000 to 2020 and to assess glacier ice thickness. The results show that the glacier surface velocity in the Mt.Tomur region showed a significant slowdown during 2000–2020, from 6.71 ± 0.66 m a−1 to 3.95 ± 0.66 m a−1, an overall decrease of 41.13%. The maximum glacier ice thickness in the Mt.Tomur region was estimated based on the ice flow principle being 171.27 ± 17.10 m, and the glacier average thickness is 50.00 ± 5.0 m. Glacier thickness at first increases with increasing altitude, showing more than 100 ± 10 m ice thickness between 3400 m and 4300 m, and then decreases with further increases in altitude. The reliability of the surface velocity and ice thickness obtained from remote sensing was proved using the measured surface velocity and ice thickness of Qingbingtan glacier No. 72 stall (the correlation coefficient R2 > 0.85). The debris cover has an overall mitigating effect on the ablation and movement rate of Qingbingtan Glacier No. 72; however, it has an accelerating effect on the ablation and movement rate of glacier No. 74.
Multimodal and Multitemporal Land Use/Land Cover Semantic Segmentation on Sentinel-1 and Sentinel-2 Imagery: An Application on a MultiSenGE Dataset
Authors: Wenger Romain , Puissant Anne , Weber Jonathan , Idoumghar Lhassane , Forestier Germain
Published: December 2022

In the context of global change, up-to-date land use land cover (LULC) maps is a major challenge to assess pressures on natural areas. These maps also allow us to assess the evolution of land cover and to quantify changes over time (such as urban sprawl), which is essential for having a precise understanding of a given territory. Few studies have combined information from Sentinel-1 and Sentinel-2 imagery, but merging radar and optical imagery has been shown to have several benefits for a range of study cases, such as semantic segmentation or classification. For this study, we used a newly produced dataset, MultiSenGE, which provides a set of multitemporal and multimodal patches over the Grand-Est region in France. To merge these data, we propose a CNN approach based on spatio-temporal and spatio-spectral feature fusion, ConvLSTM+Inception-S1S2. We used a U-Net base model and ConvLSTM extractor for spatio-temporal features and an inception module for the spatio-spectral features extractor. The results show that describing an overrepresented class is preferable to map urban fabrics (UF). Furthermore, the addition of an Inception module on a date allowing the extraction of spatio-spectral features improves the classification results. Spatio-spectro-temporal method (ConvLSTM+Inception-S1S2) achieves higher global weighted F1Score than all other methods tested.
SPV-SSD: An Anchor-Free 3D Single-Stage Detector with Supervised-PointRendering and Visibility Representation
Authors: Yin Lingmei , Tian Wei , Wang Ling , Wang Zhiang , Yu Zhuoping
Published: December 2022

Recently, 3D object detection based on multi-modal sensor fusion has been increasingly adopted in automated driving and robotics. For example, the semantic information provided by cameras and the geometric information provided by light detection and ranging (LiDAR) are fused to perceive 3D objects, as single modal sensors are unable to capture enough information from the environment. Many state-of-the-art methods fuse the signals sequentially for simplicity. By sequentially, we mean using the image semantic signals as auxiliary input for LiDAR-based object detectors would make the overall performance heavily rely on the semantic signals. Moreover, the error introduced by these signals may lead to detection errors. To remedy this dilemma, we propose an approach coined supervised-PointRendering to correct the potential errors in the image semantic segmentation results by training auxiliary tasks with fused features of the laser point geometry feature, the image semantic feature and a novel laser visibility feature. The laser visibility feature is obtained through the raycasting algorithm and is adopted to constrain the spatial distribution of fore- and background objects. Furthermore, we build an efficient anchor-free Single Stage Detector (SSD) powered by an advanced global-optimal label assignment to achieve a better time–accuracy balance. The new detection framework is evaluated on the extensively used KITTI and nuScenes datasets, manifesting the highest inference speed and at the same time outperforming most of the existing single-stage detectors with respect to the average precision.
Extraction of Winter Wheat Planting Area Based on Multi-Scale Fusion
Authors: Li Weiguo , Zhang Hong , Li Wei , Ma Tinghuai
Published: December 2022

It is difficult to accurately identify the winter wheat acreage in the Jianghuai region of China, and the fusion of high-resolution images and medium-resolution image data can improve the image quality and facilitate the identification and acreage extraction of winter wheat. Therefore, the objective of this study is to improve the accuracy of China’s medium-spatial resolution image data (environment and disaster monitoring and forecasting satellite data, HJ-1/CCD) in extracting the large area of winter wheat planted. The fusion and object-oriented classification of the 30 m × 30 m HJ-1/CCD multispectral image and 2 m × 2 m GF-1 panchromatic image (GF-1/PMS) of winter wheat at the jointing stage in the study area were studied. The GF-1/PMS panchromatic images were resampled at 8 m, 16 m and 24 m to produce panchromatic images with four spatial resolutions, including 2 m. They were fused with HJ-1/CCD multispectral images by Gram Schmidt (GS). The quality of the fused images was evaluated to pick adequate scale images for the field pattern of winter wheat cultivation in the study area. The HJ-1/CCD multispectral image was resampled to obtain an image with the same scale as the suitable scale fused image. In the two images, the training samples SFI (samples of fused image) and SRI (samples of resampled image) containing spectral and texture information were selected. The fused image (FI) and resampled image (RI) were used for winter wheat acreage extraction using an object-oriented classification method. The results indicated that the fusion effect of 16 m × 16 m fused image was better than 2 m × 2 m, 8 m × 8 m and 24 m × 24 m fused images, with mean, standard deviation, average gradient and correlation coefficient values of 161.15, 83.01, 4.55 and 0.97, respectively. After object-oriented classification, the overall accuracy of SFI for the classification of resampled image RI16m was 92.22%, and the Kappa coefficient was 0.90. The overall accuracy of SFI for the classification of fused image FI16m was 94.44%, and the Kappa coefficient was 0.93. The overall accuracy of SRI for the classification of resampled image RI16m was 84.44%, and the Kappa coefficient was 0.80. The classification effect of SFI for the fused image FI16m was the best, indicating that the object-oriented classification method combined with the fused image and the extraction samples of the fused image (SFI) could extract the winter wheat planting area with precision. In addition, the object-oriented classification method combining resampled images and the extraction samples of fused images (SFI) could extract the winter wheat planting area more effectively. These results indicated that the combination of medium spatial resolution HJ-1/CCD images and high spatial resolution GF-1 satellite images could effectively extract the planting area information of winter wheat in large regions.
Accuracy of Rockfall Volume Reconstruction from Point Cloud Data—Evaluating the Influences of Data Quality and Filtering
Authors: Walton Gabriel , Weidner Luke
Published: December 2022

Rockfall processes are now commonly studied through monitoring campaigns using repeat lidar scanning. Accordingly, several recent studies have evaluated how the temporal resolution of data collection and various data-processing decisions can influence the apparent rockfall volumes estimated using typical rockfall database creation workflows. However, there is a lack of studies that consider how data quality and associated data-processing decisions influence rockfall volume estimation. In this work, we perform a series of tests based on an existing reference rockfall database from the Front Range of Colorado, USA, to isolate the influences of data resolution (point spacing), individual point precision, and the filter threshold applied to change results, on the volume estimates obtained for rockfalls. While the effects of individual point precision were found to be limited for typical levels of gaussian noise (standard deviation per coordinate direction ≤ 0.02 m), data resolution and change filter threshold were found to have systematic impacts on volume estimates, with the volume estimates for the smallest rockfalls decreasing substantially with increases in point spacing and change filter threshold. Because these factors disproportionately impact volume estimates for smaller rockfalls, when these factors change, the slope of the apparent power law that describes the relative frequency-volume distribution of rockfalls changes. Evidence is presented that suggests that this phenomenon can explain discrepancies between power law slopes presented in the literature based on studies focused on different scales of rockfall activity. Overall, this study demonstrates the impacts of raw data attributes on rockfall volume estimation and presents an additional effect that tends to bias rockfall frequency–magnitude power law relationships towards underestimation of the relative prevalence of small rockfalls.
Integrated Mechano-Electrochemical Harvesting Fiber and Thermally Responsive Artificial Muscle for Self-Powered Temperature–Strain Dual-Parameter Sensor
Authors: Sim Hyeon Jun , Noh Jun Ho , Choi Jin Hyeong , Choi Changsoon
Published: December 2022

Significant progress in healthcare fields around the world has inspired us to develop a wearable strain–temperature sensor that can monitor biomedical signals in daily life. This novel self-powered temperature–strain dual-parameter sensor comprises a mechano-electrochemical harvester (MEH) and a thermally responsive artificial muscle (TAM). The MEHTAM system generates electricity from strain and thermal fluctuations. In addition, the sensor is comfortable to wear, owing to its stretchability (>100%), softness (<3 MPa), and one-dimensional fibers (diameter 230 μm). The MEH induces a change in the electrochemical capacitance, resulting in an electrical signal under applied strain (34 μA/m) and stress (20 μA/(m·MPa)). The TAM can be used as a mechanical temperature sensor, because the tensile stroke responds linearly to changes in temperature. As the harvester and artificial muscle are combined, the MEHTAM system generates electricity, owing to external and internal mechanical stimuli caused by muscle contractions as a response to temperature changes. The MEHTAM system that we have developed—a self-powered, strain–temperature dual-parameter sensor that is soft, stretchable, and fiber-shaped—is an interesting candidate for the production of comfortable, wearable, dual-parameter sensors.
Compact GC-QEPAS for On-Site Analysis of Chemical Threats
Authors: Liberatore Nicola , Viola Roberto , Mengali Sandro , Masini Luca , Zardi Federico , Elmi Ivan , Zampolli Stefano
Published: December 2022

This paper reports on a compact, portable, and selective chemical sensor for hazardous vapors at trace levels, which is under development and validation within the EU project H2020 “RISEN”. Starting from the prototype developed for a previous EU project, here, we implemented an updated two-stage purge and trap vapor pre-concentration system, a more compact MEMS- based fast gas-chromatographic separation module (Compact-GC), a new miniaturized quartz-enhanced photoacoustic spectroscopy (QEPAS) detector, and a new compact laser source. The system provides two-dimensional selectivity combining GC retention time and QEPAS spectral information and was specifically designed to be rugged, portable, suitable for on-site analysis of a crime scene, with accurate response in few minutes and in the presence of strong chemical background. The main upgrades of the sensor components and functional modules will be presented in detail, and test results with VOCs, simulants of hazardous chemical agents, and drug precursors will be reported and discussed.
A New Approach to Optimize SVM for Insulator State Identification Based on Improved PSO Algorithm
Authors: Song Lepeng , Liang Qin , Chen Hui , Hu Hao , Luo Yu , Luo Yanling
Published: December 2022

The failure of insulators may seriously threaten the safe operation of the power system, where the state detection of high-voltage insulators is a must for the normal and safe operation of the power system. Based on the data of insulators in aerial images, this work explored an enhanced particle swarm algorithm to optimize the parameters of the support vector machine. A support vector machine model was therefore established for the identification of the normal and defective states of the insulators. This methodology works with the structure minimization principle of SVM and the characteristics of particle swarm fast optimization. First, the aerial insulator image was segmented as a target by way of the seed region growth based on double-layer cascade morphological improvements, and then, HOG features plus GLCM features were extracted as sample data. Finally, an ameliorated PSO-SVM classifier was designed to realize insulator state identification. Comparisons were made between PSO-SVM and conventional machine learning algorithms, SVM and Random Forest, and an optimization algorithm, Gray Wolf Optimization Support Vector Machine (GWO-SVM), and advanced neural network CNN. The experimental results showed that the performance of the algorithm proposed in this paper touched the top level, where the recognition accuracy rate was 92.11%, the precision rate 90%, the recall rate 94.74%, and the F1-score 92.31%.
The Procedure of Identifying the Geometrical Layout of an Exploited Railway Route Based on the Determined Curvature of the Track Axis
Authors: Koc Wladyslaw
Published: December 2022

This paper presents a detailed algorithm for determining the curvature of a track axis with the use of a moving chord method, and then discusses the procedure for identifying the geometric layout of an exploited railway route on the basis of the determined curvature. In the moving chord method, the measured coordinates of the track axis allow one to directly determine the existence of the horizontal curvature without the need for additional measurements. This enables comprehensively identifying the existing geometric elements—straight lines, circular arcs, and transition curves. The conducted activities were illustrated with a calculation example, including a 5.5 km long test section with five areas of directional change. This showed a sequential procedure that led to the solution of the given problem. Based on the curvature diagram, the coordinates of the segmentation points, which define the connections of the existing geometric elements with each other, were determined.
Pocketable Biosensor Based on Quartz-Crystal Microbalance and Its Application to DNA Detection
Authors: Yoshimine Hiroshi , Sasaki Kai , Furusawa Hiroyuki
Published: December 2022

Quartz-crystal microbalance (QCM) is a technique that can measure nanogram-order masses. When a receptor is immobilized on the sensor surface of a QCM device, the device can detect chemical molecules captured by the mass change. Although QCM devices have been applied to biosensors that detect biomolecules without labels for biomolecular interaction analysis, most highly sensitive QCM devices are benchtop devices. We considered the fabrication of an IC card-sized QCM device that is both portable and battery-powered. Its miniaturization was achieved by repurposing electronic components and film batteries from smartphones and wearable devices. To demonstrate the applicability of the card-sized QCM device as a biosensor, DNA-detection experiments were performed. The card-sized QCM device could detect specific 10-mer DNA chains while discerning single-base differences with a sensitivity similar to that of a conventional benchtop device. The card-sized QCM device can be used in laboratories and in various other fields as a mass sensor.
Demonstration Laboratory of Industry 4.0 Retrofitting and Operator 4.0 Solutions: Education towards Industry 5.0
Authors: Ruppert Tamás , Darányi András , Medvegy Tibor , Csereklei Dániel , Abonyi János
Published: December 2022

One of the main challenges of Industry 4.0 is how advanced sensors and sensing technologies can be applied through the Internet of Things layers of existing manufacturing. This is the so-called Brownfield Industry 4.0, where the different types and ages of machines and processes need to be digitalized. Smart retrofitting is the umbrella term for solutions to show how we can digitalize manufacturing machines. This problem is critical in the case of solutions to support human workers. The Operator 4.0 concept shows how we can efficiently support workers on the shop floor. The key indicator is the readiness level of a company, and the main bottleneck is the technical knowledge of the employees. This study proposes an education framework and a related Operator 4.0 laboratory that prepares students for the development and application of Industry 5.0 technologies. The concept of intelligent space is proposed as a basis of the educational framework, which can solve the problem of monitoring the stochastic nature of operators in production processes. The components of the intelligent space are detailed through the layers of the IoT in the form of a case study conducted at the laboratory. The applicability of indoor positioning systems is described with the integration of machine-, operator- and environment-based sensor data to obtain real-time information from the shop floor. The digital twin of the laboratory is developed in a discrete event simulator, which integrates the data from the shop floor and can control the production based on the simulation results. The presented framework can be utilized to design education for the generation of Industry 5.0.
Design and Implementation of Machine Tool Life Inspection System Based on Sound Sensing
Authors: Liu Tsung-Hsien , Chi Jun-Zhe , Wu Bo-Lin , Chen Yee-Shao , Huang Chung-Hsun , Chu Yuan-Sun
Published: December 2022

The main causes of damage to industrial machinery are aging, corrosion, and the wear of parts, which affect the accuracy of machinery and product precision. Identifying problems early and predicting the life cycle of a machine for early maintenance can avoid costly plant failures. Compared with other sensing and monitoring instruments, sound sensors are inexpensive, portable, and have less computational data. This paper proposed a machine tool life cycle model with noise reduction. The life cycle model uses Mel-Frequency Cepstral Coefficients (MFCC) to extract audio features. A Deep Neural Network (DNN) is used to understand the relationship between audio features and life cycle, and then determine the audio signal corresponding to the aging degree. The noise reduction model simulates the actual environment by adding noise and extracts features by Power Normalized Cepstral Coefficients (PNCC), and designs Mask as the DNN’s learning target to eliminate the effect of noise. The effect of the denoising model is improved by 6.8% under Short-Time Objective Intelligibility (STOI). There is a 3.9% improvement under Perceptual Evaluation of Speech Quality (PESQ). The life cycle model accuracy before denoising is 76%. After adding the noise reduction system, the accuracy of the life cycle model is increased to 80%.
Improved Individualized Patient-Oriented Depth-of-Hypnosis Measurement Based on Bispectral Index
Authors: Karer Gorazd , Škrjanc Igor
Published: December 2022

Total intravenous anesthesia is an anesthesiologic technique where all substances are injected intravenously. The main task of the anesthesiologist is to assess the depth of anesthesia, or, more specifically, the depth of hypnosis (DoH), and accordingly adjust the dose of intravenous anesthetic agents. However, it is not possible to directly measure the anesthetic agent concentrations or the DoH, so the anesthesiologist must rely on various vital signs and EEG-based measurements, such as the bispectral (BIS) index. The ability to better measure DoH is directly applicable in clinical practice—it improves the anesthesiologist’s assessment of the patient state regarding anesthetic agent concentrations and, consequently, the effects, as well as provides the basis for closed-loop control algorithms. This article introduces a novel structure for modeling DoH, which employs a residual dynamic model. The improved model can take into account the patient’s individual sensitivity to the anesthetic agent, which is not the case when using the available population-data-based models. The improved model was tested using real clinical data. The results show that the predictions of the BIS-index trajectory were improved considerably. The proposed model thus seems to provide a good basis for a more patient-oriented individualized assessment of DoH, which should lead to better administration methods that will relieve the anesthesiologist’s workload and will benefit the patient by providing improved safety, individualized treatment, and, thus, alleviation of possible adverse effects during and after surgery.
Camera Arrangement Optimization for Workspace Monitoring in Human–Robot Collaboration
Authors: Oščádal Petr , Kot Tomáš , Spurný Tomáš , Suder Jiří , Vocetka Michal , Dobeš Libor , Bobovský Zdenko
Published: December 2022

Human–robot interaction is becoming an integral part of practice. There is a greater emphasis on safety in workplaces where a robot may bump into a worker. In practice, there are solutions that control the robot based on the potential energy in a collision or a robot re-planning the straight-line trajectory. However, a sensor system must be designed to detect obstacles across the human–robot shared workspace. So far, there is no procedure that engineers can follow in practice to deploy sensors ideally. We come up with the idea of classifying the space as an importance index, which determines what part of the workspace sensors should sense to ensure ideal obstacle sensing. Then, the ideal camera positions can be automatically found according to this classified map. Based on the experiment, the coverage of the important volume by the calculated camera position in the workspace was found to be on average 37% greater compared to a camera placed intuitively by test subjects. Using two cameras at the workplace, the calculated positions were 27% more effective than the subjects’ camera positions. Furthermore, for three cameras, the calculated positions were 13% better than the subjects’ camera positions, with a total coverage of more than 99% of the classified map.
Magnetomechanical Properties of Fe-Si-B and Fe-Co-Si-B Metallic Glasses by Various Annealing Temperatures for Actuation Applications
Authors: Sun Yu , Zhang Xu , Wu Sheng , Zhuang Xin , Yan Bin , Zhu Wanhua , Dolabdjian Christophe , Fang Guangyou
Published: December 2022

Fe-based amorphous alloys have advantages of low iron loss and high effective permeability, which are widely used in sensors and actuators. Power efficiency is one of the most important indicators among power conversion applications. We compared the magnetomechancial power conversion factors of metallic glassy ribbons FeCoSiB (Vitrovac 7600) and FeSiB (Metglas 2605SA1). We investigated the crystallization process under different annealing temperatures and tested the magnetomechancial coupling factors (k) and quality factors (Q) by using resonant and anti-resonant methods. We found that the maximum coupling factor of the annealed Vitrovac ribbons was 23% and the figure of merits k2Q was 4–7; however, the maximum coupling factor of the annealed Metglas ribbons was 73% and the maximum value of k2Q was 16. We can observe that the Metglas 2605SA1 ribbons have higher values of the magnetomechanical power efficiency than those of the Vitrovac 7600 ribbons, which means they are better to be used in subsequent research regarding acoustically driven antennas.