bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluation of Polyphenolic Composition and Antimicrobial Properties of Sanguisorba officinalis L. and Sanguisorba minor Scop.
Authors: Tocai (Moţoc) Alexandra-Cristina , Ranga Floricuta , Teodorescu Andrei George , Pallag Annamaria , Vlad Andreea Margareta , Bandici Livia , Vicas Simona Ioana
Published: December 2022

The most widespread Sanguisorba species are Sanguisorba officinalis L. and Sanguisorba minor Scop. which are also found in the Romanian flora and classified as medicinal plants because of hemostatic, antibacterial, antitumor, antioxidant and antiviral activities. This study aimed to characterize and compare Sanguisorba species in order to highlight which species is more valuable according to phenolic profile and antimicrobial activity. Based on high-performance liquid chromatography equipped with photodiode array detection and mass spectrometry (electrospray ionization) (HPLC–DAD-MS (ESI+)) analysis, it was evident that the ethanol extract obtained from the leaves of S. minor Scop. contains the highest content of phenolic compounds at 160.96 mg/g p.s., followed by the flower and root extract (131.56 mg/g dw and 121.36 mg/g dw, respectively). While in S. officinalis, the highest amount of phenols was recorded in the root extract (127.06 mg/g), followed by the flower and leaves extract (102.31 mg/g and 81.09 mg/g dw, respectively). Our results show that among the two species, S. minor Scop. is richer in phenolic compounds compared with the S. officinalis L. sample. In addition, the antimicrobial potential of each plant organ of Sanguisorba species was investigated. The ethanol extract of S. minor Scop. leaves exhibited better antibacterial activity against all of the bacteria tested, especially on Staphylococcus aureus, with an inhibition zone of 15.33 ± 0.83 mm. Due to the chemical composition and antimicrobial effect, the Sanguisorba species can be used as food supplements with beneficial effects on human health.
Priming by Insects: Differential Effects of Sympatric and Allopatric Priming upon Plant Performance and Tolerance to Herbivory
Authors: Garrido Etzel , Boege Karina , Domínguez César A. , Fornoni Juan
Published: December 2022

Plants have evolved multiple mechanisms to defend themselves from their multiple herbivores. Thus, being able to recognise among them and respond accordingly is fundamental for plant survival and reproduction. Defence priming prepares the plant to better or more rapidly respond to future damage; however, while it is considered an adaptive trait, to date, no studies have evaluated the extent and specificity of the priming recognition. To estimate the costs, benefits and specificity of priming, we used a highly specialist plant–insect system (Datura stramonium–Lema daturaphila) and performed a reciprocal transplant experiment with two populations where a priming stimulus (sympatric vs. allopatric) and a damage treatment (sympatric) were applied. We found no evidence of a fitness cost of priming, given that primed plants without damage showed no reduction in fitness. In contrast, our treatments affected the probability of bud abortion. That is, when damaged plants received no priming or the priming came from an allopatric insect, the likelihood of aborting the first bud was 1.9 times greater compared to plants being primed by their sympatric insect. We also found that damaged plants primed with an allopatric insect produced 14% fewer seeds compared to plants receiving a sympatric priming stimulus. Tolerance to herbivore damage was also the lowest when plants received the priming stimulus from an allopatric insect. Overall, these results suggest that, in our study system, plants recognise their local insect population reducing the negative effect of damage through a tolerance response.
Potato (Solanum tuberosum L.) Plant Shoot and Root Changes under Abiotic Stresses—Yield Response
Authors: Mańkowska Dominika Boguszewska- , Zarzyńska Krystyna , Wasilewska-Nascimento Beata
Published: December 2022

During the growing season, potato plants are often exposed to soil drought, frequently accompanied by heat stress, which results in crop losses. In our experiment, the impact of these stresses, both separately and simultaneously, on the above-ground, on the root, and on the tuber mass was assessed. Four potato cultivars were tested. In vitro plants were planted in plastic tubes. Four treatments were used: control–optimal irrigation and temperature (22/18 °C), drought stress, high temperature stress (38/25 °C), and drought and high temperature stresses combined. The stresses were applied for two weeks during the tuberization phase. Both stresses caused changes in plant morphology. Drought stress had a greater impact on these changes than high temperatures. The biggest changes, however, took place when both stresses were applied simultaneously. Under all stresses, a decrease in tuber yield was found. The largest decrease was recorded in the case of applying both stresses simultaneously, while the smallest one was in the case of high temperature stress in relation to a control condition. Among the morphological parameters studied, the mass of the root system and its share in the entire biomass of the plant had the greatest impact on the decrease in yield. This mainly concerned drought stress.
Severe Shoot Trimming and Crop Size as Tools to Modulate Cv. Merlot Berry Composition
Authors: Bubola Marijan , Persic Martina , Rossi Sara , Bestulić Ena , Zdunić Goran , Plavša Tomislav , Radeka Sanja
Published: December 2022

Viticulture production is challenged by climate change and the consequent higher accumulation of carbohydrates in grapevine berries, resulting in high-alcoholic wines. This study investigates the application of severe shoot trimming performed at three different stages and crop size management as tools for the modulation of cv. Merlot berry composition, aimed at reducing the sugar content in the berry. In the first study, the effects of severe shoot trimming carried out at three different phenological stages were studied. In the second study, late severe shoot trimming was combined with two crop sizes and regulated by shoot thinning. The obtained results demonstrated that severe shoot trimming in earlier stages of berry development limited the accumulation of both sugars and anthocyanins as compared to the control treatment. However, when severe shoot trimming was performed at late veraison (at approximately 14 Brix), it decreased only the accumulation of sugars, without affecting the accumulation of anthocyanins. The results of the second study showed that the modification of crop size by shoot thinning significantly affected the measured yield parameters, whereas the effect on Brix and anthocyanins was seasonally dependent. It was concluded that among the studied techniques, severe shoot trimming at late veraison is the most effective way to reduce sugar content in the berry without affecting the accumulation of anthocyanins.
Antimicrobial, Antibiofilm, and Antioxidant Properties of Essential Oil of Foeniculum vulgare Mill. Leaves
Authors: Di Napoli Michela , Castagliuolo Giusy , Badalamenti Natale , Maresca Viviana , Basile Adriana , Bruno Maurizio , Varcamonti Mario , Zanfardino Anna
Published: December 2022

Foeniculum vulgare (Apiaceae) is an aromatic fennel with important practices in medicinal and traditional fields, used in the treatment of digestive complications, and gastrointestinal and respiratory disorders. Its leaves and stems, tender and fresh, are used in the production of pasta dressing and main courses, while its seeds, with a strong smell of anise, are excellent flavoring for baked goods, meat dishes, fish, and alcoholic beverages. The aim of this work is concerning the extraction of essential oil (EO) from the leaves of F. vulgare subsp. vulgare var. vulgare, investigating antimicrobial, antibiofilm, and antioxidant efficacy. In particular, GC-MS analysis showed how the chemical composition of EO was influenced by the massive presence of monoterpene hydrocarbons (α-pinene 33.75%) and phenylpropanoids (estragole 25.06%). F. vulgare subsp. vulgare var. vulgare EO shows excellent antimicrobial activity against both Gram-positive and Gram-negative strains. This EO can inhibit biofilm formation at very low concentrations and has a good ability to scavenge oxygen radicals in vitro. F. vulgare subsp. vulgare var. vulgare EO also has an increased activity of superoxide dismutase (SOD), catalase (CAT) and glutathione peroxidase (GPx) enzymes and decreased ROS levels in zymosan opsonized PMNs (OZ).
Integrated Biorefinery and Life Cycle Assessment of Cassava Processing Residue–From Production to Sustainable Evaluation
Authors: Andrade Larissa Renata Santos , Felisardo Raul José Alves , Cruz Ianny Andrade , Bilal Muhammad , Iqbal Hafiz M. N. , Mulla Sikandar I. , Bharagava Ram Naresh , Souza Ranyere Lucena de , Azevedo Lucas Carvalho Basilio , Ferreira Luiz Fernando Romanholo
Published: December 2022

Commonly known as a subsistence culture, cassava came to be considered a commodity and key to adding value. However, this tuber’s processing for starch and flour production is responsible for generating a large amount of waste that causes serious environmental problems. This biomass of varied biochemical composition has excellent potential for producing fuels (biogas, bioethanol, butanol, biohydrogen) and non-energetic products (succinic acid, glucose syrup, lactic acid) via biorefinery. However, there are environmental challenges, leading to uncertainties related to the sustainability of biorefineries. Thus, the provision of information generated in life cycle assessment (LCA) can help reduce bottlenecks found in the productive stages, making production more competitive. Within that, this review concentrates information on the production of value-added products, the environmental impact generated, and the sustainability of biorefineries.
Growth Parameters of Various Green Microalgae Species in Effluent from Biogas Reactors: The Importance of Effluent Concentration
Authors: Ziganshina Elvira E. , Bulynina Svetlana S. , Yureva Ksenia A. , Ziganshin Ayrat M.
Published: December 2022

The use of liquid waste as a feedstock for cultivation of microalgae can reduce water and nutrient costs and can also be used to treat wastewater with simultaneous production of biomass and valuable products. This study applied strategies to treat diluted anaerobic digester effluent (ADE) as a residue of biogas reactors with moderate (87 ± 0.6 mg L−1; 10% ADE) and elevated NH4+-N levels (175 ± 1.1 mg L−1; 20% ADE). The effect of ADE dilution on the acclimatization of various microalgae was studied based on the analysis of the growth and productivity of the tested green algae. Two species of the genus Chlorella showed robust growth in the 10–20% ADE (with a maximum total weight of 3.26 ± 0.18 g L−1 for C. vulgaris and 2.81 ± 0.10 g L−1 for C. sorokiniana). The use of 10% ADE made it possible to cultivate the strains of the family Scenedesmaceae more effectively than the use of 20% ADE. The growth of Neochloris sp. in ADE was the lowest compared to other microalgal strains. The results of this study demonstrated the feasibility of introducing individual green microalgae into the processes of nutrient recovery from ADE to obtain biomass with a high protein content.
Isolation and Characterization of Flavonoid Naringenin and Evaluation of Cytotoxic and Biological Efficacy of Water Lilly (Nymphaea mexicana Zucc.)
Authors: Din Shajrath , Hamid Saima , Yaseen Aadil , Yatoo Ali Mohd , Ali Shafat , Shamim Kashif , Mahdi Wael A. , Alshehri Sultan , Rehman Muneeb U. , Shah Wajaht A.
Published: December 2022

Despite its limited exploration, Nymphaea mexicana Zucc. can be beneficial if pharmacology, isolation, and biological evaluation are given attention. It is an aquatic species that belongs to the family Nymphaeaceae. The thrust area of the work was the extraction, isolation, and biological evaluation of different extracts of the N. mexicana Zucc. plant. The primary goal of this research was to assess the antimicrobial, antioxidant, and anticancer activities of the extracts and to isolate the target naringenin compound. Comparative FT IR analysis of different extracts of this plant revealed the presence of functional groups of plant secondary metabolites, including polyphenols, flavonoids, terpenoids, esters, amines, glycosides, alkanes, alkaloids, fatty acids, and alcohols. Moderate free radical scavenging potential has been achieved for the various extracts via reducing power and DPPH assays. While cytotoxic activity was evaluated by colorimetric and lactate dehydrogenase cell viability tests on potent cancer cell lines. Lung adenocarcinoma epithelial cells (A-549), and breast cells (MC-7) were treated with MeOH extract. The antimicrobial activity against bacterial strains was evaluated using Gram-positive and -negative cultures, where maximum and minimum inhibition zones were recorded for different strains, including 1.6–25.6 μg/mL for Streptococcus aureus, using the agar well diffusion method. In addition, the anti-inflammatory activity of different extracts of N. mexicana Zucc. was evaluated in a nitrite radical scavenging assay with high concentrations of secondary metabolites, which are important against human pathogens and other diseases.
Fabrication and Characterization of Hydrogen Peroxide and Thymol-Loaded PVA/PVP Hydrogel Coatings as a Novel Anti-Mold Surface for Hay Protection
Authors: Malka Eyal , Caspi Ayelet , Cohen Reut , Margel Shlomo
Published: December 2022

Animal food source production is increasing due to the growing world population. Many sources (e.g., hay) are prone to mold development, resulting in food degradation. This study proposes an environmentally friendly anti-mold fungicide comprising hydrogen peroxide (HP) and thymol entrapped in a polyvinyl alcohol/pyrrolidone (PVA/PVP) hydrogel (PVA is biodegradable and PVP is water soluble and non-toxic) coated on a polyethylene (PE) films for preservative hay packaging. The hydrogels improved the thermal stability of the entrapped HP and thymol, resulting in a prolonged release into the hay and thereby increasing anti-mold activity. The hydrogel composition and morphology, thymol and HP thermal stability, and release rates through indirect (gas phase) contact were investigated. Fungicidal capabilities were tested, indicating wide-range efficiency against mold growth on hay with a clear advantage for the thymol-loaded hydrogels. No visual side effects were observed on hay exposed to the released fumes of HP and/or thymol. These results demonstrate the potential of thymol-loaded hydrogels as effective and safe post-harvest preservatives.
Fabrication of Inorganic Coatings Incorporated with Functionalized Graphene Oxide Nanosheets for Improving Fire Retardancy of Wooden Substrates
Authors: Tasi Tsung-Pin , Hsieh Chien-Te , Yang Hsi-Chi , Huang Heng-Yu , Wu Min-Wei , Ashraf Gandomi Yasser
Published: December 2022

Flame-retardant chemicals are frequently used within consumer products and can even be employed as a treatment on the surface of different types of materials (e.g., wood, steel, and textiles) to prevent fire or limit the rapid spread of flames. Functionalized graphene oxide (FGO) nanosheets are a promising construction coating nanomaterial that can be blended with sodium metasilicate and gypsum to reduce the flammability of construction buildings. In this work, we designed and fabricated novel and halogen-free FGO sheets using the modified Hummers method; and subsequently functionalized them by pentaerythritol through a chemical impregnation process before dispersing them within the construction coating. Scanning electron microscopic images confirm that the FGO-filled coating was uniformly dispersed on the surface of wooden substrates. We identified that the FGO content is a critical factor affecting the fire retardancy. Thermogravimetric analysis of the FGO coating revealed that higher char residue can be obtained at 700 °C. Based on the differential scanning calorimetry, the exothermic peak contained a temperature delay in the presence of FGO sheets, primarily due to the formation of a thermal barrier. Such a significant improvement in the flame retardancy confirms that the FGO nanosheets are superior nanomaterials to be employed as a flame-retardant construction coating nanomaterial for improving thermal management within buildings.
Starch Biocryogel for Removal of Methylene Blue by Batch Adsorption
Authors: Taweekarn Tarawee , Wongniramaikul Worawit , Boonkanon Chanita , Phanrit Chonthicha , Sriprom Wilasinee , Limsakul Wadcharawadee , Towanlong Wanchitra , Phawachalotorn Chanadda , Choodum Aree
Published: December 2022

A green monolithic starch cryogel was prepared and applied for the removal of methylene blue (MB) using a batch system. The influence of various experimental parameters on MB adsorption was investigated. High removal efficiency (81.58 ± 0.59%) and adsorption capacity (34.84 mg g−1) were achieved. The Langmuir model better fitted the experimental data (determination coefficient (R2) = 0.9838) than the Freundlich one (R2 = 0.8542), while the kinetics of MB adsorption on the cryogel followed a pseudo-second-order model. The adsorption process was spontaneous and endothermic with an activation energy of 37.8 kJ mol−1 that indicated physical adsorption. The starch cryogel was used for MB removal from a wastewater sample collected from a local Batik production community enterprise in Phuket, Thailand, and a removal efficiency of 75.6% was achieved, indicating that it has a high potential as a green adsorbent for MB removal.
Melt Temperature Estimation by Machine Learning Model Based on Energy Flow in Injection Molding
Authors: Jeon Joohyeong , Rhee Byungohk , Gim Jinsu
Published: December 2022

Highly reliable and accurate melt temperature measurements in the barrel are necessary for stable injection molding. Conventional sheath-type thermocouples are insufficiently responsive for measuring melt temperatures during molding. Herein, machine learning models were built to predict the melt temperature after plasticizing. To supply reliably labeled melt temperatures to the models, an optimized temperature sensor was developed. Based on measured high-quality temperature data, three machine learning models were built. The first model accepted process setting parameters as inputs and was built for comparisons with previous models. The second model accepted additional measured process parameters related to material energy flow during plasticizing. Finally, the third model included the specific heat and part weights reflecting the material energy, in addition to the features of the second model. Thus, the third model outperformed the others, and its loss decreased by more than 70%. Meanwhile, the coefficient of determination increased by about 0.5 more than those of the first model. To reduce the dataset size for new materials, a transfer learning model was built using the third model, which showed a high prediction performance and reliability with a smaller dataset. Additionally, the reliability of the input features to the machine learning models were evaluated by shapley additive explanations (SHAP) analysis.
An Experimental Investigation into Mechanical and Thermal Properties of Hybrid Woven Rattan/Glass-Fiber-Reinforced Epoxy Composites
Authors: Irawan Agustinus Purna , Anggarina Paula Tjatoerwidya , Utama Didi Widya , Najid Najid , Abdullah Mohd Zulkfly , Siregar Januar Parlaungan , Cionita Tezara , Fitriyana Deni Fajar , Jaafar Jamiluddin , Hadi Agung Efriyo , Rihayat Teuku
Published: December 2022

The investigation of hybrid, woven, natural fiber-reinforced polymer composites as a substitute reinforcement for fiber polymer composites has recently caught the interest of academics, industry, and researchers. Woven, natural fiber composites have been implemented in many different applications, including parts for automobiles, household items, flooring, aerospace, and ballistic materials. Therefore, this research seeks to establish the thermal and mechanical characteristics of composites made from rattan strips (RS) and glass fiber (GF)-reinforced epoxy resin (ER). Other than that, the impact of layering configurations with respect to the thermal and mechanical characteristics of the RS and GF will be determined. Hand lay-up and a hydraulic press machine produce hybrid, woven RS and GF laminates. The hybrid composite’s mechanical properties will be investigated using impact, tensile, and flexural tests. The hybrid woven of the GF/RS/RS/RS/GF composite sequence demonstrated the highest mechanical properties in comparison to other sequences. The increase from one to three layers of RS in the core layer of GF hybrid composites enhanced the flexural, impact, and tensile properties. In addition, the hybridization of rattan and GF is more thermally stable, as recorded by the high decomposition temperature. As a finding of the research, the woven RS and GF hybrid is a potential material for automotive applications such as car bumpers, for example.
The Influence of Ply Stacking Sequence on Mechanical Properties of Carbon/Epoxy Composite Laminates
Authors: Ogunleye Raphael Olabanji , Rusnakova Sona , Zaludek Milan , Emebu Samuel
Published: December 2022

In this work, the effect of ply stacking sequence of carbon/epoxy laminates subjected to flexural, tensile and impact loading was investigated. Five laminates with different stacking configurations were produced using the hand-laying-up technique. This includes a unidirectional laminate, cross-ply laminates, and quasi-isotropic laminates. Following the autoclave curing process, the responses of the composites to bending, tension and impact force were determined according to ASTM standards, and their corresponding strength, stiffness as well as impact energy were evaluated. Likewise, the flexural failure mode associated with each laminate was characterised using an optical microscope. The unidirectional laminates have higher flexural and tensile strength compared to the cross-ply and quasi-isotropic laminates. Moreover, as a result of material symmetry, the flexural and tensile modulus of symmetric cross-ply laminate improved by 59.5% and 3.97% compared to the unsymmetric counterpart. Furthermore, the quasi-isotropic laminates with absorption energy of 116.2 kJ/m2 and 115.12 kJ/m2, respectively have higher impact resistance compared to other samples.
Small-Angle X-ray Scattering Analysis on the Estimation of Interaction Parameter of Poly(n-butyl acrylate)-b-poly(methyl methacrylate)
Authors: Lee Sang-In , Seo Min-Guk , Huh June , Paik Hyun-jong
Published: December 2022

The temperature dependence of the Flory–Huggins interaction parameter χ for poly(n-butyl acrylate)-b-poly(methyl methacrylate) (PBA-b-PMMA) was quantified from small-angle X-ray scattering (SAXS) analysis using random phase approximation (RPA) theory. It was found from the χ estimation (χ=0.0103+14.76/T) that the enthalpic contribution, χH, a measure for temperature susceptibility of χ, is 1.7–4.5 folds smaller for PBA-b-PMMA than for the conventional styrene-diene-based block copolymers, which have been widely used for thermoplastic elastomers. This finding suggests that these fully acrylic components can be a desirable chemical pair for constituting terpolymers applied for thermally stable and mechanically resilient elastomers.
Study of the Synthetic Approach Influence in Ni/CeO2-Based Catalysts for Methane Dry Reforming
Authors: Pizzolato Marco , Da Pian Giulia , Ghedini Elena , Di Michele Alessandro , Menegazzo Federica , Cruciani Giuseppe , Signoretto Michela
Published: December 2022

This study focuses on the synthetic approach influence in morphostructural features and catalytic performances for Ni/CeO2 catalysts. Incipient wetness impregnation, coprecipitation and nitrate combustion were studied as catalyst preparation approaches, and the materials were then tested at 700 °C for methane dry reforming (MDR). The morphostructural properties of the materials were deeply studied using several techniques, such as temperature programmed reduction (TPR), to investigate reducibility and support-metal interaction, N2 physisorption to evaluate the porosity and the surface area, scanning electron microscopy (SEM) and X-ray diffraction (XRD) to estimate Ni dispersion, and temperature programmed oxidation (TPO) to identify the type and amount of coke formed on catalysts’ surface after reaction. From the data obtained, coprecipitation turned out to be the most suitable technique for this application because this catalyst was able to reach 70% of CO2 conversion and 30% methane conversion, with an H2 yield of 15% and 30% yield of CO at the end of the 30 h test. Moreover, it was also the catalyst with the highest metal dispersion, the strongest interaction with the support, and the lowest coke deposition.
The Virgin Mary and Sainte-Foy: Chant and the Original Design of the West Façade at Conques
Authors: Pentcheva Bissera V.
Published: December 2022

Using the evidence of Aquitanian chants, this article explores the possibility that a twelfth-century relief panel of the Annunciation today in the interior of Conques was originally designed for the West facade, where it completes the composition of the divine plan of Salvation. This hypothetic reconstruction also uncovers the important role of the patron saint, Sainte-Foy, and how she is promoted as second after Mary and efficacious intercessor.
A Method for Retrieving Cloud-Top Height Based on a Machine Learning Model Using the Himawari-8 Combined with Near Infrared Data
Authors: Dong Yan , Sun Xuejin , Li Qinghui
Published: December 2022

Different cloud-top heights (CTHs) have different degrees of atmospheric heating, which is an important factor for weather forecasting and aviation safety. AHIs (Advanced Himawari Imagers) on the Himawari-8 satellite are a new generation of visible and infrared imaging spectrometers characterized by a wide observation range and a high temporal resolution. In this paper, a cloud-top height retrieval algorithm based on XGBoost is proposed. The algorithm comprehensively utilizes AHI L1 multi-channel radiance data and calculates the input parameters of the generated model according to the characteristics of the cloud phase, texture, and the local brightness temperature change of the cloud. In addition, the latitude, longitude, solar zenith angle and satellite zenith angle are input into the model to further constrain the influence of the geographical and spatial factors such as the sea and land location, on CTH. Compared with the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) cloud-top height data (CTHCAL), the results show that: the algorithm retrieved the cloud-top height (CTHXGB) with a mean error (ME) of 0.3 km, a standard deviation (Std) of 1.72 km, and a root mean square error (RMSE) of 1.74 km. Additionally, it improves the problem of the large systematic deviation in the cloud-top height products released by the Japan Meteorological Agency (CTHJMA), especially for ice clouds and multi-layer clouds with ice clouds on the top layer. For water clouds below 2 km and multi-layer clouds with water clouds at the top, the algorithm solves the systematically serious CTHJMA problem. XGBoost can effectively distinguish between different cloud scenarios within the model, which is robust and suitable for CTH retrieval.
A Lightweight Privacy-Preserving System for the Security of Remote Sensing Images on IoT
Authors: Zhang Denghui , Ren Lijing , Shafiq Muhammad , Gu Zhaoquan
Published: December 2022

The acquisition of massive remote sensing data makes it possible to deeply fuse remote sensing and artificial intelligence (AI). The mobility and cost advantages of new sensing platforms in the Internet of Things (IoT) make them ideal for continuous deployment rather than traditional airborne platforms. However, remote sensing devices are vulnerable to malicious attacks and privacy leaks when sharing data due to the complex architecture and heterogeneity of IoT and the lack of a unified security protection mechanism. Traditional protection methods based on public-key encryption require not only complex operations but also energy consumption, which poses new challenges for resources-limited IoT. The objective of this paper was to propose a lightweight privacy-preserving system for the security of remote-sensing images based on visual cryptography. This stacking-to-see feature of visual cryptography enables the efficient encryption of big data such as high-resolution and multi-scale remote sensing images in resource-constrained IoT. To alleviate image quality degradation in visual cryptography, we combined denoising neural networks to extract high-quality images from encrypted datasets, thus improving the recognition accuracy of loss datasets. We conducted extensive experiments, and the results verify the effectiveness of the proposed method in terms of privacy protection and classification accuracy.
Evaluation of Hybrid Wavelet Models for Regional Drought Forecasting
Authors: Hinge Gilbert , Piplodiya Jay , Sharma Ashutosh , Hamouda Mohamed A. , Mohamed Mohamed M.
Published: December 2022

Drought forecasting is essential for risk management and preparedness of drought mitigation measures. The present study aims to evaluate the effectiveness of the proposed hybrid technique for regional drought forecasting. Multiple Linear Regression (MLR), Artificial Neural Network (ANN), and two wavelet techniques, namely, Discrete Wavelet Transform (DWT) and Wavelet Packet Transform (WPT), were evaluated in drought forecasting up to a lead time of six months. Standard error metrics were used to select optimal model parameters, such as number of inputs, number of hidden neurons, level of decomposition, and number of mother wavelets. Additionally, the performance of various mother wavelets, including the Haar wavelet (db1) and 19 Daubechies wavelets (db1 to db20), were evaluated. The results indicated that the ANN model produced better forecasts than the MLR model, whereas the hybrid models outperformed both ANN and MLR models, which failed to predict the SPI values for a lead time greater than two months. The performance of all the models was found to improve as the timescale increased from 3 to 12 months. However, all the models’ performances deteriorated as the lead time increased. The hybrid WPT-MLR was the best model for the study area. The findings indicated that a hybrid WPT-MLR model could be used for drought early warning systems in the study area.
A Novel GB-SAR System Based on TD-MIMO for High-Precision Bridge Vibration Monitoring
Authors: Zhang Zexi , Suo Zhiyong , Tian Feng , Qi Lin , Tao Haihong , Li Zhenfang
Published: December 2022

Ground-based synthetic aperture radar (GB-SAR) is a highly effective technique that is widely used in landslide and bridge deformation monitoring. GB-SAR based on multiple input multiple output (MIMO) technology can achieve high accuracy and real-time detection performance. In this paper, a novel method is proposed to design transmitting and receiving array elements, which increases the minimum spacing of the antenna by sacrificing several equivalent phase centers. In MIMO arrays, the minimum antenna spacing in the azimuth direction is doubled, which increases the variety of antenna options for this design. To improve the accuracy of the system, a new method is proposed to estimate channel phase errors, amplitude errors, and position errors. The position error is decomposed into three directions with one compensated by the phase error and two estimated by the strong point. Finally, we validate the accuracy of the system and our error estimation method through simulations and experiments. The results prove that the GB-SAR system performs well in bridge deformation and vibration monitoring with the proposed method.
Locating Earth Disturbances Using the SDR Earth Imager
Authors: Sharif Radwan , Tanyer Suleyman Gokhun , Harrison Stephen , Junor William , Driessen Peter , Herring Rodney
Published: December 2022

The Radio Wave Phase Imager uses monitoring and recording concepts, such as Software Defined Radio (SDR), to image Earth’s atmosphere. The Long Wavelength Array (LWA), New Mexico Observatory is considered a high-resolution camera that obtains phase information about Earth and space disturbances; therefore, it was employed to capture radio signals reflected from Earth’s F ionization layer. Phase information reveals and measures the properties of waves that exist in the ionization layer. These waves represent terrestrial and solar Earth disturbances, such as power losses from power generating and distribution stations. Two LWA locations were used to capture the ionization layer waves, including University of New Mexico’s Long Wavelength Array’s LWA-1 and LWA-SV. Two locations of the measurements showed wavevector directions of disturbances, whereas the intersection of wavevectors determined the source of the disturbance. The research described here focused on measuring the ionization layer wave’s phase shifts, frequencies, and wavevectors. This novel approach is a significant contribution to determine the source of any disturbance.
Development and Assessment of Seasonal Rainfall Forecasting Models for the Bani and the Senegal Basins by Identifying the Best Predictive Teleconnection
Authors: Balcázar Luis , Bâ Khalidou M. , Díaz-Delgado Carlos , Gómez-Albores Miguel A. , Gaona Gabriel , Minga-León Saula
Published: December 2022

The high variability of rainfall in the Sahel region causes droughts and floods that affect millions of people every year. Several rainfall forecasting models have been proposed, but the results still need to be improved. In this study, linear, polynomial, and exponential models are developed to forecast rainfall in the Bani and Senegal River basins. All three models use Atlantic sea surface temperature (SST). A fourth algorithm using stepwise regression was also developed for the precipitation estimates over these two basins. The stepwise regression algorithm uses SST with covariates, mean sea level pressure (MSLP), relative humidity (RHUM), and five El Niño indices. The explanatory variables SST, RHUM, and MSLP were selected based on principal component analysis (PCA) and cluster analysis to find the homogeneous region of the Atlantic with the greatest predictive ability. PERSIANN-CDR rainfall data were used as the dependent variable. Models were developed for each pixel of 0.25° × 0.25° spatial resolution. The second-order polynomial model with a lag of about 11 months outperforms all other models and explains 87% of the variance in precipitation over the two watersheds. Nash–Sutcliffe efficiency (NSE) values were between 0.751 and 0.926 for the Bani River basin and from 0.175 to 0.915 for the Senegal River basin, for which the lowest values are found in the driest area (Sahara). Results showed that the North Atlantic SST shows a more robust teleconnection with precipitation dynamics in both basins.
Drought Monitoring and Performance Evaluation Based on Machine Learning Fusion of Multi-Source Remote Sensing Drought Factors
Authors: Zhao Yangyang , Zhang Jiahua , Bai Yun , Zhang Sha , Yang Shanshan , Henchiri Malak , Seka Ayalkibet Mekonnen , Nanzad Lkhagvadorj
Published: December 2022

Drought is an extremely dangerous natural hazard that causes water crises, crop yield reduction, and ecosystem fires. Researchers have developed many drought indices based on ground-based climate data and various remote sensing data. Ground-based drought indices are more accurate but limited in coverage; while the remote sensing drought indices cover larger areas but have poor accuracy. Applying data-driven models to fuse multi-source remote sensing data for reproducing composite drought index may help fill this gap and better monitor drought in terms of spatial resolution. Machine learning methods can effectively analyze the hierarchical and non-linear relationships between the independent and dependent variables, resulting in better performance compared with traditional linear regression models. In this study, seven drought impact factors from the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite sensor, Global Precipitation Measurement Mission (GPM), and Global Land Data Assimilation System (GLDAS) were used to reproduce the standard precipitation evapotranspiration index (SPEI) for Shandong province, China, from 2002 to 2020. Three machine learning methods, namely bias-corrected random forest (BRF), extreme gradient boosting (XGBoost), and support vector machines (SVM) were applied as regression models. Then, the best model was used to construct the spatial distribution of SPEI. The results show that the BRF outperforms XGBoost and SVM in SPEI estimation. The BRF model can effectively monitor drought conditions in areas without ground observation data. The BRF model provides comprehensive drought information by producing a spatial distribution of SPEI, which provides reliability for the BRF model to be applied in drought monitoring.
A Novel Method for Simulating Micro-Scale Water Droplet Movements
Authors: Lin Zhijie , Hu Zhongtian , Lou Senyu , Guo Lingling , Chen Jingjing
Published: December 2022

Micro-scale fluids are tiny droplets that adhere to the surface of an object as a result of rainfall, perspiration, etc. Micro-scale fluid simulation is widely used in fields such as film and games. The existing state-of-the-art simulation methods are not suitable for simulating water droplets moving on a surface due to the fact that the water droplets cannot leave the texture space and their movements always depend on the continuous UV region. In this study, a novel method for simulating water droplets moving on a surface is proposed. We divide the droplets into two types: (1) two-dimensional droplets and (2) three-dimensional droplets and we implement the transformation between two-dimensional droplets in the texture space and three-dimensional droplets in the physical space. In the preprocessing phase, jump textures, coordinate transform textures and force field textures are generated in the non-continuous UV regions on a 3D object’s surface. In the process of simulation, water droplets are treated as rigid particles. The Velocity-Verlet-based method is adopted to solve the motion trajectory equation, and the boundary droplet transport algorithm is implemented based on jump texture. In the process of rendering, the height map is generated according to the simulation in the texture space and then the liquid bridge phenomenon between the droplets is simulated based on the Gaussian blur and the color rank algorithm. Finally, they are converted into normal texture-rendering droplets. The experimental result shows that the proposed method works well when simulating the movements of water droplets on a surface in a real-time manner, and it makes the movement simulation of dimension-reducing water droplets no longer depend on the continuous surface and continuous UV region. Moreover, the simulation efficiency of the proposed method is two times higher than that of the Smoothed Particle Hydrodynamics (SPH) method.
Getting Smarter: Blockchain and IOT Mixture in China Smart Public Services
Authors: Boustani Nada Mallah , Xu Qing , Xu Yan
Published: December 2022

Due to tremendous technological breakthroughs, an increasing number of cities are transforming into “smart cities” utilizing the Internet of Things (IOT), artificial intelligence, or other information technologies. The Chinese government announced that the development of “digital cities smart cities” was a national priority. The goal of this study is to examine the success variables that can influence IOT service adoption aspirations while also serving as a mediator for enhanced security via blockchain technologies. A conceptual model is created with a strong theoretical underpinning and body of literature. The final sample consisted of 1008 participants. This study uses the partial least squares structural equation modelling (PLS-SEM model) to test and analyze the impact of identified variables on the continuous usage intention (CUI) of IOT-based public services. Our findings show that blockchain adoption in smart cities fully mediates the effect of the IOT on CUI and shed the light on the importance of the trust, empowerment, and social influence since the continuous usage intention of the IOT in smart cities is mainly influenced by these factors and enhanced by the application of blockchain.
Digitalization of Educational Organizations: Evaluation and Improvement Based on DigCompOrg Model
Authors: Fernández-Miravete Ángel David , Prendes-Espinosa Paz
Published: December 2022

The digitalization of educational organizations is a political and social priority at European level and the model which is the basis for the analysis is DigCompOrg as part of the European Framework of Competences. This article summarizes the results of a longitudinal evaluative research (from 2018 until 2022) around the digitalization process of a compulsory secondary education center. We have applied a mixed method and an evaluative research design based on the use of questionnaires, focus groups and a research diary. This article is focused on data from the last evaluation (2021–2022) where the participants are 26 members of the management team, 46 teachers and 374 students. Our results show that progress has been made in the digitalization process, especially in some areas such as leadership, infrastructure/equipment and pedagogy/support/resources, which have obtained high scores. On the other hand, the data also show other areas where there is more scope for improvement, such as collaboration, digital networks and also innovative assessment practices. This research can be valuable as an example of a good practice around the digitalization of institutions of formal education.
Impact of COVID and the Emergence of Social Emotional Learning on Education Majors
Authors: Kardambikis Patricia , Donne Vicki
Published: December 2022

In March of 2020, institutions of higher education sent their students home and moved their classroom instruction online. While this prevented the spread of COVID, it caused students to face unique challenges impacting their social emotional needs and mental health. As college students returned to campus, they had to learn to navigate a “new normal”. Social emotional needs and mental health continue to be affected, which can significantly impair student’s academic success and ultimately affect their future career and personal opportunities. This was particularly true for candidates enrolled in teacher preparation programs as they attempted to navigate the changing environments of both K-12 schools and higher education. Core components of teacher preparation programs are field experiences and student teaching. With the closure of schools and/or move to provide virtual instruction, clinical experiences for teacher candidates were impacted. The changing educational environments required teacher candidates to exhibit strong social emotional skills and to develop those skills in their K-12 students. A survey was conducted to examine perceptions of students majoring in education on their transition from high school to higher education and the impact of COVID on their academic performance and social and emotional well-being.
Policies in Need of a Problem? A Qualitative Study of Medical and Nonmedical Opioid Use among College Student-Athletes in the United States
Authors: McLean Katherine
Published: December 2022

Concern around nonmedical opioid use (NUPO) among student-athletes in the United States abounds, yet research around NUPO in this population is mixed. While some studies have identified athletic participation and related injury as risk factors for NUPO, the balance of research has found the inverse, or no association. This study represents the first qualitative inquiry into college student-athletes’ history of injury, medical and nonmedical opioid exposure, and pain management practices. Drawing on surveys (n = 280) and interviews (n = 30) with less-elite (i.e., non-NCAA Division I) athletes attending a large state university, our analyses documented little NUPO in this population, despite significant rates of injury and opioid prescription. Interview participants evinced little knowledge, but high fears, around opioid use, while describing potentially harmful levels of over-the-counter drug use. Overall, this study suggests the need for the development of broad, evidence-based curricula concerning pharmacological pain management within this population.
Introduction to Crises, (Im)mobilities and Young Life Trajectories
Authors: Donà Giorgia , Veale Angela
Published: December 2022

This Special Issue on Crisis, (Im)mobilities and Young Life Trajectories examines the intersections of developmental trajectories and (im)mobility amidst crises, with a focus on ruptures, transitions, disruptions and continuities in the life course of children and young people who have been forced to move due to various man-made and natural crises [...]
Global Assessment of Groundwater Stress Vis-à-Vis Sustainability of Irrigated Food Production
Authors: Mohan Chinchu , Western Andrew W. , Jha Madan Kumar , Wei Yongping
Published: December 2022

Due to poor water resources management, groundwater-dependent agriculture induces substantial stress on several aquifer systems worldwide, which poses a serious threat to water and food security. However, only a few studies have addressed this vital issue. This study aimed to evaluate stress on aquifers due to the overuse of groundwater for food production and explore pathways for stress reduction via improved irrigation efficiency and productivity. Groundwater stress was characterized using the ratio of water use to availability, with consideration for environmental flows. The results indicated that out of 107 countries—dependent on groundwater irrigation, about half are overexploiting groundwater, while one-fifth of these countries are extracting moderately-to heavily. Over 90% of the non-renewable groundwater abstraction occurs in 7 countries. Further, about 450 million tonnes (Mt) of global annual food production is from non-renewable groundwater exploitation. If the existing irrigation efficiency is increased to 90%, current groundwater stress would be reduced by 40%. Additionally, in unstressed regions, it would be possible to produce additional 300 Mt of food by using saved water while maintaining groundwater stress at acceptable levels. Moreover, improved water productivity in conjunction with increased irrigation efficiency could reduce the current level of unsustainable food production by 47%. These results provide important insights into the dynamics of irrigation stress on groundwater systems, and the role of managerial interventions.