bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluation of the Antimicrobial, Thermal, Mechanical, and Barrier Properties of Corn Starch–Chitosan Biodegradable Films Reinforced with Cellulose Nanocrystals
Authors: Díaz-Cruz Claudio Alonso , Caicedo Carolina , Jiménez-Regalado Enrique Javier , Díaz de León Ramón , López-González Ricardo , Aguirre-Loredo Rocio Yaneli
Published: May 2022

Packaging materials play an essential role in the preservation and marketing of food and other products. To improve their conservation capacity, antimicrobial agents that inhibit bacterial growth are used. Biopolymers such as starch and chitosan are a sustainable alternative for the generation of films for packaging that can also serve as a support for preservatives and antimicrobial agents. These substances can replace packaging of synthetic origin and maintain good functional properties to ensure the quality of food products. Films based on a mixture of corn starch and chitosan were developed by the casting method and the effect of incorporating cellulose nanocrystals (CNC) at different concentrations (0 to 10% w/w) was studied. The effect of the incorporation of CNC on the rheological, mechanical, thermal and barrier properties, as well as the antimicrobial activity of nanocomposite films, was evaluated. A significant modification of the functional and antimicrobial properties of the starch–chitosan films was observed with an increase in the concentration of nanomaterials. The films with CNC in a range of 0.5 to 5% presented the best performance. In line with the physicochemical characteristics which are desired in antimicrobial materials, this study can serve as a guide for the development this type of packaging for food use.
Experimental Evaluation of Carbon Reinforced TRC with Cement Suspension Matrix at Elevated Temperature
Authors: Fürst Richard , Hejtmánek Petr , Vlach Tomáš , Řepka Jakub , Mózer Vladimír , Hájek Petr
Published: May 2022

Textile-reinforced concrete (TRC) is a new composite material comprising high-performance concrete and textile reinforcement from textile yarns with a matrix, usually consisting of epoxy resins (ER). The most significant advantage of ER is the homogenization of all filaments in the yarn and full utilization of its tensile potential. Nevertheless, ER matrix is a critical part of TRC design from the perspective of the fire resistance due to its relatively low resistance at temperatures of approximately 120 ∘C. This work expands the previously performed mechanical tests at normal temperatures with cement suspension (CS) as a non-combustible material for the yarn matrix. Here, the mechanical properties of CS matrix at elevated temperatures were verified. It was found that the addition of polypropylene fibers into HPC negatively affected the mechanical results of CS matrix specimens. Simultaneously, thermal insulation effect of the covering layers with different thicknesses did not significantly influence the residual bending strength of specimens with CS matrix and achieved similar results as reference specimens. Furthermore, all specimens with ER matrix progressively collapsed. Finally, CS as a textile reinforcement of yarn matrix appears to be a suitable solution for increasing the temperature resistance of TRC structures and for substituting synthetic resins.
Construction and Evaluation of Chitosan-Based Nanoparticles for Oral Administration of Exenatide in Type 2 Diabetic Rats
Authors: Yang Jian-Miao , Wu Lin-Jie , Lin Meng-Ting , Lu Yi-Ying , Wang Tian-Tian , Han Min , Zhang Bin , Xu Dong-Hang
Published: May 2022

Oral delivery of therapeutic peptides has been a daunting challenge due to poor transport across the tight junctions and susceptibility to enzymatic degradation in the gastrointestinal tract. Numerous advancement in nanomedicine has been made for the effective delivery of protein and peptide. Owing to the superior performance of chitosan in opening intercellular tight junctions of epithelium and excellent mucoadhesive properties, chitosan-based nanocarriers have recently garnered considerable attention, which was formulated in this paper to orally deliver the GLP-1 drug (Exenatide). Against this backdrop, we used chitosan (CS) polymers to encapsulate the exenatide, sodium tripolyphosphate (TPP) as the cross-linking agent and coated the exterior with sodium alginate (ALG) to impart the stability in an acidic environment. The chitosan/alginate nanoparticles (CS-TPP-ALG) functioned as a protective exenatide carrier, realized efficient cellular uptake and controlled release, leading to a steady hypoglycemic effect and a good oral bioavailability in vivo. Trimethyl chitosan (TMC), a chitosan derivative with stronger positive electrical properties was additionally selected as a substitute for chitosan to construct the TMC-TPP-ALG nanoparticle, and its oral peptide delivery capacity was explored in terms of both characterization and pharmacodynamics studies. Overall, our study demonstrated that functional chitosan/alginate nanoparticles can protect proteins from enzymatic degradation and enhance oral absorption, which presents important research value and application prospects.
Frequency Response of Thermo-Optic Phase Modulators Based on Fluorinated Polyimide Polymer Waveguide
Authors: Lee Eun-Su , Chun Kwon-Wook , Jin Jinung , Oh Min-Cheol
Published: May 2022

Polymer waveguide phase modulators exhibit stable low-power phase modulation owing to their exceptional thermal confinement and high thermo-optic effect, and thus, have the merit of thermal isolation between channels, which is crucial for an optical phased array (OPA) beam scanner device. In this work, a waveguide phase modulator was designed and fabricated based on a high-refractive-index fluorinated polyimide. The propagation loss of the polyimide waveguide and the temporal response of the phase modulator were characterized. Moreover, the transfer function of the phase modulator including multiple poles and zeros was obtained from the measured frequency response. The polyimide waveguide modulator device demonstrated a fast response time of 117 μs for 1 kHz input signal, however, for 1 mHz step-function input, it exhibited an additional 5% phase change in 5 s.
Synthesis and Application of Reactive Acrylic Latexes: Effect of Particle Morphology
Authors: Cheaburu-Yilmaz Catalina N. , Ozkan Cigdem Kilicarislan , Yilmaz Onur
Published: May 2022

The aim of the study is the synthesis and characterization of epoxy functional reactive polyacrylic latexes, e.g., poly (BA-co-MMA-co-AN-co-GMA) with core/shell and non-structured (random) particle morphologies. Additionally, their performance as binders and coating ability in leather finishing were studied. The epoxy functional polymers were synthesized via the seeded emulsion polymerization technique and the obtained latexes were characterized by means of particle size, zeta potential, FTIR, TEM, DSC, DMTA, and TGA. The results showed that the particle size and zeta potential values were very similar for both latexes, except core/shell latex had slightly higher particle size. DSC, TEM, and DMTA studies verified the successful synthesis of core/shell latex morphology. The copolymer films were elastic in nature and had low Tg values (−13 and −20 °C). The performance results showed some different behavior for core/shell and random copolymer coatings. The abrasion resistance of the leather finish with random copolymer as binder exhibited slightly better values, especially in wet conditions. On the other hand, the leathers finished with core/shell binder showed better performance in flexing endurance and the water spotting test.
Carbon Fiber/PLA Recycled Composite
Authors: Al Zahmi Salem , Alhammadi Saif , ElHassan Amged , Ahmed Waleed
Published: May 2022

Due exceptional properties such as its high-temperature resistance, mechanical characteristics, and relatively lower price, the demand for carbon fiber has been increasing over the past years. The widespread use of carbon-fiber-reinforced polymers or plastics (CFRP) has attracted many industries. However, on the other hand, the increasing demand for carbon fibers has created a waste recycling problem that must be overcome. In this context, increasing plastic waste from the new 3D printing technology has been increased, contributing to a greater need for recycling efforts. This research aims to produce a recycled composite made from different carbon fiber leftover resources to reinforce the increasing waste of Polylactic acid (PLA) as a promising solution to the growing demand for both materials. Two types of leftover carbon fiber waste from domestic industries are handled: carbon fiber waste (CF) and carbon fiber-reinforced composite (CFRP). Two strategies are adopted to produce the recycled composite material, mixing PLA waste with CF one time and with CFRP the second time. The recycled composites are tested under tensile test conditions to investigate the impact of the waste carbon reinforcement on PLA properties. Additionally, thermogravimetric analysis (TGA), X-ray diffraction (XRD), and Fourier-transformed infrared spectroscopy (FTIR) is carried out on composites to study their thermal properties.
Relation between Droplet Size Distributions and Physical Stability for Zein Microfluidized Emulsions
Authors: Santos Jenifer , Trujillo-Cayado Luis Alfonso , Carrillo Francisco , López-Castejón María Luisa , Alfaro-Rodríguez María Carmen
Published: May 2022

Zein, a subproduct of the food industry and a protein, possesses limited applications due to its high hydrophobic character. The objective of this research was to investigate the influence of homogenization pressure and cycles on the volumetric mean diameter (D4,3), span values, and Turbiscan Stability Index (TSI) using the response surface methodology for microfluidized emulsions containing zein as a unique stabilizer. Results showed that homogenization pressure seems to be the most influential parameter to obtain enhanced physical stability and droplet size distributions, with the optimum being 20,000 psi. Interestingly, the optimum number of cycles for volumetric diameter, span value, and TSI is not the same. Although a decrease of D4,3 with number of cycles is observed (optimum three cycles), this provokes an increase of span values (optimum one cycle) due to the recoalescence effect. Since physical stability is influenced by D4,3 and span, the minimum for TSI is observed at the middle level of the cycles (2 cycles). This work highlights that not only volumetric diameter, but also span value must be taken into consideration in order to obtain stable zein emulsions. In addition, this study wants to extend the limited knowledge about zein-based emulsions processed with a Microfluidizer device.
Cooperative Effect of ZIF-67-Derived Hollow NiCo-LDH and MoS2 on Enhancing the Flame Retardancy of Thermoplastic Polyurethane
Authors: Qian Yi , Su Wenyuan , Li Long , Zhao Rongmin , Fu Haoyan , Li Jiayin , Zhang Peidong , Guo Qingjie , Ma Jingjing
Published: May 2022

In this work, a novel three-dimensional (3D) hollow nickel-cobalt layered double hydroxide (NiCo-LDH) was synthesized using zeolitic imidazole framework-67 (ZIF-67) as a template, and then utilized to functionalize molybdenum disulfide (NiCo-LDH/MoS2) via electrostatic force. Flame retardant thermoplastic polyurethane (TPU) composites were prepared by the melt blending method. Compared to pure TPU, NiCo-LDH/MoS2 filled TPU composite was endowed with a decrease of 30.9% and 55.7% of the peak heat release rate (PHRR) and the peak smoke production rate (PSPR), respectively. Furthermore, the addition of NiCo-LDH/MoS2 can significantly improve the thermal stability and char yield of the TPU composite. The catalytic carbonization effect and dilution effect of NiCo-LDH, and the barrier effect of MoS2 nanosheets enable TPU composites with excellent flame retardancy and toxic gas suppression ability.
Effects of Reed Biochar Mass Fraction on the Properties of Polypropylene/Reed Char Composites
Authors: Ye Yunpeng , Zou Dongfang , Si Shuang , Li Xingong
Published: May 2022

Reed charcoal/polypropylene (RC/PP) composites were prepared by melt-blending and molding processes. The effects of RC addition (by mass fraction) on its mechanical properties were investigated and the mechanism characterized. The results showed that RC and PP were physically bonded and formed a mechanical interlocking matrix. The water absorption rate of these composites was <1% at 168 h. As the RC mass fraction increased, the tensile modulus, crystallinity, and energy storage modulus of the composites increased and then decreased, with the tensile modulus reaching a maximum of 679.4 MPa. The thermal decomposition rate peak and starting melt temperature increased by 14.8 and 2.5 °C, respectively, compared to pure PP, and the energy storage modulus reached a maximum of 3752.8 MPa at 40 wt% RC. The addition of RC in appropriate amounts improved the rigidity and thermal stability of these composites.
An Efficient Technique for Ammonia Capture in the Haber–Bosch Process Loop—Membrane-Assisted Gas Absorption
Authors: Petukhov Anton N. , Atlaskin Artem A. , Smorodin Kirill A. , Kryuchkov Sergey S. , Zarubin Dmitriy M. , Atlaskina Maria E. , Petukhova Anastasia N. , Stepakova Anna N. , Golovacheva Anna A. , Markov Artem N. , Stepanova Ekaterina A. , Vorotyntsev Andrey V. , Vorotyntsev Ilya V.
Published: May 2022

The present study continues the development and enhancement of a highly efficient unique hybrid technique—membrane-assisted gas absorption in designing the separation unit, which provides the improvement in mass-transfer of a target component during the ammonia capture process from a process loop of the Haber–Bosch technological route. In order to minimize the absorbent volume to membrane area ratio, the special separation cell was designed based on a combination of two types of hollow fiber membranes, dense gas separation membrane and porous pervaporation membrane. The separation performance tests were implemented under two sets of conditions, sweeping the bore (permeate) side of a cell with helium and hydrogen-nitrogen mix. For both cases, the membrane-assisted gas absorption cell demonstrated high separation efficiency, and the ammonia concentration in the permeate was never lower than 81 mol%; meanwhile, under the hydrogen-nitrogen bore sweep conditions, the ammonia concentration in the permeate reached 97.5 mol% in a single-step process. Nevertheless, there is a product purity–recovery rate trade-off, which is a typical issue for separation processes.
Triazole-Functionalized Mesoporous Materials Based on Poly(styrene-block-lactic acid): A Morphology Study of Thin Films
Authors: Trejo-Maldonado Melisa , Womiloju Aisha , Stumpf Steffi , Hoeppener Stephanie , Schubert Ulrich S. , Elizalde Luis E. , Guerrero-Sanchez Carlos
Published: May 2022

We report the synthesis of poly(styrene-block-lactic acid) (PS-b-PLA) copolymers with triazole rings as a junction between blocks. These materials were prepared via a ‘click’ strategy which involved the reaction between azide-terminated poly(styrene) (PS-N3) and acetylene-terminated poly(D,L-lactic acid) (PLA-Ac), accomplished by copper-catalyzed azide-alkyne cycloaddition reaction. This synthetic approach has demonstrated to be effective to obtain specific copolymer structures with targeted self-assembly properties. We observed the self-assembly behavior of the PS-b-PLA thin films as induced by solvent vapor annealing (SVA), thermal annealing (TA), and hydrolysis of the as-spun substrates and monitored their morphological changes by means of different microscopic techniques. Self-assembly via SVA and TA proved to be strongly dependent on the pretreatment of the substrates. Microphase segregation of the untreated films yielded a pore size of 125 nm after a 45-min SVA. After selectively removing the PLA microdomains, the as-spun substrates exhibited the formation of pores on the surface, which can be a good alternative to form an ordered pattern of triazole functionalized porous PS at the mesoscale. Finally, as revealed by scanning electron microscopy–energy dispersive X-ray spectroscopy, the obtained triazole-functionalized PS-porous film exhibited some affinity to copper (Cu) in solution. These materials are suitable candidates to further study its metal-caption properties.
Investigation of Physical and Mechanical Characteristics of Rubber Materials Exposed to High-Pressure Hydrogen
Authors: Jeon Sang Koo , Jung Jae Kap , Chung Nak Kwan , Baek Un Bong , Nahm Seung Hoon
Published: May 2022

Rubber materials play a key role in preventing hydrogen gas leakage in high-pressure hydrogen facilities. Therefore, it is necessary to investigate rubber materials exposed to high-pressure hydrogen to ensure operational safety. In this study, permeation, volume swelling, hydrogen content, and mechanical characteristics of acrylonitrile butadiene rubber (NBR), ethylene propylene diene monomer (EPDM), and fluorocarbon (FKM) samples exposed to pressures of 35 and 70 MPa were investigated. The results showed that the volume recovery and hydrogen desorption behavior of EPDM with the highest permeation were fast whereas those of FKM with the lowest permeation were slow. The volume of NBR with the highest hydrogen content expanded after decompression. In contrast, FKM swelled the most despite having the lowest hydrogen content. After exposure to high-pressure hydrogen, the compression set (CS) slightly increased due to internal cracks, but the tensile strength decreased significantly with increasing pressure despite the absence of cracks in the fracture area of all tensile specimens. It was concluded that the decrease in tensile strength is closely related to the volume increase because of the relationship between the relative true strength and the volume ratio.
Mechanical and Physical Properties of Particleboard Made from the Sumatran Elephant (Elephas maximus sumatranus) Dung and Wood Shaving
Authors: Hartono Rudi , Dalimunthe Ahmad , Iswanto Apri , Herawati Evalina , Sutiawan Jajang , de Azevedo Afonso
Published: May 2022

Sumatran elephants (Elephas maximus sumatranus) are the world’s largest living land mammals. The elephant’s digestive system can only absorb 40% of the nutrients in digested feed, and the remainder is excreted as dung. Elephant dung waste can be used as a particleboard material due to its high fiber content. The objectives of this study are: (i) to prepare elephant dung waste as raw material for particleboard, (ii) to improve elephant dung particleboard’s physical and mechanical properties using wood shavings, and (iii) to study the influence of several parameters on the physical and mechanical properties of particleboard. The particleboard dimensions and density were set at 20 cm × 20 cm × 1 cm and 0.8 g/cm3, respectively. The mixture ratio of elephant dung and wood shavings was 100/0, 90/10, 80/20, 70/30, 60/40, and 50/50 (% w/w). This mixture ratio of particles was sprayed with 7% isocyanate adhesive. The pressing at a pressure of 30 kg/cm2 for 5 min and 160 °C was used in this study. The physical and mechanical properties of particleboard were tested according to JIS A 5908 (2003) standard. The result shows that the addition of wood shaving improved the elephant dung particleboard’s physical and mechanical properties. Except for moisture content and water absorption, the addition of wood shavings has a significant effect on elephant dung particleboard’s physical and mechanical properties. The best ratio of elephant dung and wood-shaving for this research is 50/50 and has fulfilled the JIS A 5908-2003 standard, except for thickness swelling.
Effect of Wettability on Vacuum-Driven Bubble Nucleation
Authors: Pradhan Sushobhan , Counts Sage , Enget Charissa , Bikkina Prem Kumar
Published: May 2022

Nucleation is the formation of a new phase that has the ability to irreversibly and spontaneously grow into a large-sized nucleus within the body of a metastable parent phase. In this experimental work, the effect of wettability on the incipiation of vacuum-driven bubble nucleation, boiling, and the consequent rate of evaporative cooling are studied. One hydrophilic (untreated), and three hydrophobic (chlorinated polydimethylsiloxane, chlorinated fluoroalkylmethylsiloxane and (heptadecafluoro-1,1,2,2-tetrahydrodecyl)triethoxysilane) glass vials of different wettabilities were filled with degassed deionized water and exposed to a controlled vacuum inside a transparent desiccator. The vacuum was increased by 34 mbar abs. (1 inHg rel.) steps with 15-min waiting period to observe bubble nucleation. The average onset pressures for gas/vapor bubble nucleation in CM, CF, and HT vials were 911 ± 30, 911 ± 34, and 925 ± 17 mbar abs., respectively. Bubble nucleation was not observed in hydrophilic vial even at 65 mbar abs. pressure. During the vacuum boiling at 65 mbar abs., the average temperatures of water in hydrophilic, CM, CF, and HT vials reduced from room temperature (~22.5 °C) to 15.2 ± 0.9, 13.1 ± 0.9, 12.9 ± 0.5, and 11.2 ± 0.3 °C, respectively. The results of this study show that the wettability of the container surface has a strong influence on the onset vacuum for vapor/gas bubble nucleation, rate of vacuum boiling, and evaporative cooling. These findings are expected to be useful to develop wettability-based vacuum boiling technologies.
Practical Application-Oriented Energy Management for a Plug-In Hybrid Electric Bus Using a Dynamic SOC Design Zone Plan Method
Authors: Han Wenxiao , Chu Xiaohua , Shi Sui , Zhao Ling , Zhao Zhen
Published: May 2022

The main problem in current energy management is the ability of practical application. To address the problem, this paper proposes a reinforcement learning (RL)-based energy management by combining Tubule Q-learning and Pontryagin’s Minimum Principle (PMP) algorithms for a plug-in hybrid electric bus (PHEB). The main innovation distinguished from the existing energy management strategies is that a dynamic SOC design zone plan method is proposed. It is characterized by two aspects: ① a series of fixed locations are defined in the city bus route and a linear SOC reference trajectory is re-planned at fixed locations; ② a triangle zone will be re-planned based on the linear SOC reference trajectory. Additionally, a one-dimensional state space is also designed to ensure the real-time control. The off-line trainings demonstrate that the agent of the RL-based energy management can be well trained and has good generalization performance. The results of hardware in loop simulation (HIL) demonstrate that the trained energy management has good real-time performance, and its fuel consumption can be decreased by 12.92%, compared to a rule-based control strategy.
Digital Twin-Driven Approach for Process Management and Traceability towards Ship Industry
Authors: Wang Kan , Hu Qianqian , Liu Jialin
Published: May 2022

The digital twin (DT) approach has risen in popularity for applications in many industrial process managements. By applying the “Shipyard 4.0” digital transformation trend, the ship industry is developing techniques able to reduce risks by improving operation process management. This study proposes a combination of a DT approach and practical experiment as part of a five-tier framework for DT-driven process management in the ship industry. This study focuses on the characteristic scenarios and crucial parameters within the ship engine system and shipping cargo container in operation procedures. DT-based models and platforms are established in this study based on the basic modeling of Maya and scene rendering of Unity 3D. To address the fusion issue of multi-source heterogeneous data in the ship operation process, a Bayesian neural network (BNN) method is introduced into DT’s virtual model layer and data support layer. By integrating an improved BNN-based algorithm into DT-based models, the collected data can be extracted and aggregated accordingly. In the ship engine room, the operating temperature is selected as a critical parameter, with the best mean percentage deviation (MPD) between DT-driven predictions and test value of 3.18%. During the shipping cargo container process, the results indicate that DT-based models have acceptable performances under different conditions, with optimal MPDs of 5.22%.
Antibacterial and Antifungal Activity of Functionalized Cotton Fabric with Nanocomposite Based on Silver Nanoparticles and Carboxymethyl Chitosan
Authors: Arenas-Chávez Carlos Alberto , de Hollanda Luciana Maria , Arce-Esquivel Arturo A. , Alvarez-Risco Aldo , Del-Aguila-Arcentales Shyla , Yáñez Jaime A. , Vera-Gonzales Corina
Published: May 2022

Cotton is the most widely used natural fiber for textiles; however, the capacity of cotton fibers to absorb large amounts of moisture, retain oxygen, and have a high specific surface area makes them more prone to microbial contamination, becoming an appropriate medium for the growth of bacteria and fungi. In recent years, the incorporation of silver nanoparticles in textile products has been widely used due to their broad-spectrum antibacterial activity and low toxicity towards mammalian cells. The aim of the current study is to continue the assessment of our developed nanocomposite and evaluate the antibacterial and antifungal activity of the nanocomposite based on silver nanoparticles and carboxymethyl chitosan (AgNPs-CMC) against Escherichia coli, Staphylococcus aureus, and Candida albicans, evaluated by the well diffusion method. The antibacterial activity against E. coli and S. aureus was also evaluated by the qualitative method of inhibition zone and the quantitative method of colony counting. Likewise, the antifungal activity of the functionalized fabric against Candida albicans and Aspergillus niger was determined by the inhibition zone method and the antifungal activity method GBT 24346-2009, respectively. The functionalized fabric showed 100% antibacterial activity against E. coli and S. aureus and good antifungal activity against C. albicans and A. niger. Our results indicate that the functionalized fabric could be used in garments for hospital use to reduce nosocomial infections.
Effects of Energetic Carbon-Cluster Ion Irradiation on Lattice Structures of EuBa2Cu3O7−x Oxide Superconductor
Authors: Iwase Akihiro , Saitoh Yuichi , Chiba Atsuya , Hori Fuminobu , Ishikawa Norito
Published: May 2022

C-axis-oriented EuBa2Cu3O7−x oxide films that were 100 nm thick were irradiated with 0.5 MeV C monoatomic ions, 2 MeV C4 cluster ions and 4 MeV C8 cluster ions at room temperature. Before and after the irradiation, X-ray diffraction (XRD) measurement was performed using Cu-Ka X-ray. The c-axis lattice constant increased almost linearly as a function of numbers of irradiating carbon ions, but it rarely depended on the cluster size. Cluster size effects were observed in the XRD peak intensity and the XRD peak width. With increasing the cluster size, the decrease in peak intensity becomes more remarkable and the peak width increases. The experimental result implies that the cluster ions with a larger size provide a more localized energy deposition in a sample, and cause larger and more inhomogeneous lattice disordering. As such, local and large lattice disordering acts as a pinning center for quantum vortex; energetic carbon-cluster ion irradiation will be effective for the increment in the critical current of EuBa2Cu3O7−x superconductors.
Building a More Inclusive Workplace for Religious Minorities
Authors: Garcia-Yeste Carme , Mara Liviu-Catalin , de Botton Lena , Duque Elena
Published: May 2022

The current secular models are putting strain on religious diversity in the context of the workplace. With religious diversity growing in European societies and the visible expression of religious beliefs and behaviors, tensions have arisen linked to the rise of xenophobia. The scientific literature shows that religious minorities are discriminated in the workplace, especially Muslim women that wear Islamic veils. Nonetheless, the people pertaining to these religious minorities have agency, and they can overcome this discrimination. This paper presents the results of a systematic literature review of scientific articles published in SCOPUS and Web of Science using the preferred reporting items for systematic reviews and meta-analyses (PRISMA). The review focuses on the management of religious diversity in labor contexts, especially regarding Muslim women wearing Islamic veils. The results identify some successfully implemented actions that contribute to more inclusive workplaces for religious minorities, especially for Muslim women wearing Islamic veils. Some of these actions are implemented from the employee perspective and include networking and mentoring, while others are implemented from a company perspective and are related to the creation of management styles that place people in the center. The crucial role that politics plays is also briefly discussed.
Xuanzang and the Three Types of Wisdom: Learning, Reasoning, and Cultivating in Yogācāra Thought
Authors: Jannel Romaric
Published: May 2022

Xuanzang (602–664) is famous for his legendary life, his important translation works, and also his Discourse on the Realisation of Consciousness-Only (Vijñapti-mātratā-siddhi, 成唯識論). This text, which is considered as a synthesis of Yogācāra thought, has been diversely interpreted by modern scholars and is still discussed, in particular about the status of external things. Nevertheless, this issue seems to be of little interest for Yogācāra thinkers compared to other topics such as the Noble Path, or else the three types of wisdom (trividhā prajñā, 三慧): learning (śruta, 聞), reasoning (cintā, 思), and cultivating (bhāvanā, 修). As emphasized in recent research, this topic represents a major issue for Buddhist practitioners. In an attempt to analyse it in Xuanzang’s Discourse, and more generally in Yogācāra thought, this paper will first discuss Asaṅga’s and Vasubandhu’s thought on the three types of wisdom. Secondly, since it is important to replace the three types of wisdom in the general argumentation of Xuanzang’s Discourse, we will present the structure of his text which is modelled on a “path” leading progressively to Supreme Awakening. Then, we will present the main elements of the Noble Path and situate the three types of wisdom into it. Finally, we will explain that Xuanzang follows Asaṅga’s and Vasubandhu’s conceptions and eventually confirm the importance of the three types of wisdom in Yogācāra thought.
Did the Prophets Teach Us to Protest?
Authors: Cataldo Jeremiah
Published: May 2022

If we pay attention to biblical prophets, we can hear in their messages a calling to seek out the liberation of the downtrodden and oppressed. Despite the common tendency to interpret biblical prophets as predictors of the future, their focus was not on the future but their present social and political environments. That means their messages are not straightforward treatises on theology. They are not universalized “truths”. They are messages that call us to be attentive to those who are downtrodden. Their prophetic critique can be read as a call to recognize the humanity in others and to be willing to enter into relational dialogue with them.
Silence and Sounds: An Autoethnography of Searching for Spirituality during Suicide Bereavement in Life and Research
Authors: Čepulienė Austėja Agnietė
Published: May 2022

In this article, I used autoethnography to describe and analyze my experience of being bereaved by suicide and researching spirituality during suicide bereavement. The culture silenced my grief, and this is congruent with the experiences of my research participants. The religious community, in my case, did not help me and added to my spiritual and psychological pain. The silenced parts of my loss started to make sounds, such as psychological disturbances, but also as unconscious and conscious choices, which led to immersing myself in the research of spirituality during suicide bereavement. Research on the topic goes hand in hand with my search for spirituality during suicide bereavement and reviewing my loss. My story suggests that despite the negative experiences with Catholic priests, spirituality during suicide bereavement can become a vital resource to find meaning for the loss and the pain of grief and can take many different and even unexpected forms.
Special Issue “Cyber Risk and Security”
Authors: Dacorogna Michel , Kratz Marie
Published: May 2022

The COVID-19 pandemic and now the war in Ukraine, have raised the risks to levels not seen in the last 30 years [...]
Determinants of Behavioral Intentions to Use Islamic Financial Technology: An Empirical Assessment
Authors: Khan Mohammad Shahfaraz , Rabbani Mustafa Raza , Hawaldar Iqbal Thonse , Bashar Abu
Published: May 2022

This study examines the antecedents/determinants of behavioral intentions toward the utilization of Islamic financial technology for Middle Eastern customers. The study applied structural equation modeling (PLS-SEM). After robust research efforts were invested in the identification of factors, they and were converted into measures, and the results were analyzed. The results demonstrate that the independent variables shown in the UTAUT model have a significant impact on the behavior to adopt Islamic financial technology, which implies that the people are ready to use Islamic financial technology while making online transactions. The work in this study adds to the knowledge regarding the factors affecting behavioral intention to use Islamic fintech, as there is scarcity of studies in this domain, especially in the context of Middle Eastern online customers. Moreover, this study also considers the major categories of online payments.
Application of Convolutional Neural Networks on Digital Terrain Models for Analyzing Spatial Relations in Archaeology
Authors: Meyer-Heß M. Fabian , Pfeffer Ingo , Juergens Carsten
Published: May 2022

Archaeological research is increasingly embedding individual sites in archaeological contexts and aims at reconstructing entire historical landscapes. In doing so, it benefits from technological developments in the field of archaeological prospection over the last 20 years, including LiDAR-based Digital Terrain Models, special visualizations, and automated site detection. The latter can generate comprehensive datasets with manageable effort that are useful for answering large-scale archaeological research questions. This article presents a highly automated workflow, in which a Convolutional Neural Network is used to detect burial mounds in the proximity of remotely located hollow ways. Detected mounds are then analyzed with respect to their distribution and a possible spatial relation to hollow ways. The detection works well, produces a reasonable number of results, and achieved a precision of at least 77%. The distribution of mounds shows a clear maximum in the radius of 2000–2500 m. This supports future research such as visibility or cost path analysis.
Pronounced Changes in Thermal Signals Associated with the Madoi (China) M 7.3 Earthquake from Passive Microwave and Infrared Satellite Data
Authors: Jing Feng , Zhang Lu , Singh Ramesh P.
Published: May 2022

Thermal variations in surface and atmosphere observed from multiple satellites prior to strong earthquakes have been widely reported ever since seismic thermal anomalies were discovered three decades ago. These thermal changes are related to stress accumulation caused by the tectonic activities in the final stage of earthquake preparation. In the present paper, we focused on the thermal changes associated with the 2021 Madoi M 7.3 earthquake in China and analyzed the temporal and spatial evolution of the Index of Microwave Radiation Anomaly (IMRA) and the Index of Longwave Radiation Anomaly (ILRA) based on 8-year microwave brightness temperature (MWBT) and 14-year outgoing longwave radiation (OLR) data collected by satellites. We also explored their responses in different tectonic units (seismogenic fault zone and active tectonic block). Our results indicated that the enhanced IMRA was distributed along the seismogenic fault since mid-February and reappeared for a longer time and with stronger intensity in March and April 2021. The pronounced enhancement in the ILRA was observed within one month over Bayan Har tectonic and adjacent blocks. The higher ILRA over the tectonic blocks in the southern Tibet Plateau at the beginning of 2021 could be associated with the regional stress accumulation, as proven by the occurrences of two moderate earthquakes during this period.
A New Approach for Adaptive GPR Diffraction Focusing
Authors: Hamdan Hamdan , Economou Nikos , Vafidis Antonis , Bano Maksim , Ortega-Ramirez Jose
Published: May 2022

Several researchers have utilized multipath summation to manage the common problem of scattered energy within GPR sections. Such energy results in degrading the lateral resolution and continuity of reflectors. If detailed velocity models are known, then it is fairly easy to focus the scattered energy by means of conventional migration methods. However, this is rarely the case in GPR sections, as the common-offset antenna array is mostly used, and therefore cannot provide velocity models. This gives an important advantage for the multipath summation method, which has proved to be successful in focusing such diffractions, without the need to build a detailed migration velocity field model. This multipath summation method is based on stacking (summation) of constant velocity migrated sections (weighted or not) over a predefined velocity range. The main drawback of this technique is the high computational cost and the need for user interference to select the appropriate stacking weights. We developed an improved implementation of the weighted multipath summation method that reduces both the computational cost, and the user interference in stacking weights selections. This data adaptive methodology can expedite the migration process, suppress the need for a detailed velocity model, and reduce the user subjectivity. Moreover, a data adaptive spectral scaling scheme was developed. This is applied on the output of the multipath summation process to reduce the expected blurriness in the resulting GPR sections.
Function-Based Troposphere Tomography Technique for Optimal Downscaling of Precipitation
Authors: Haji-Aghajany Saeid , Amerian Yazdan , Amiri-Simkooei Alireza
Published: May 2022

Precipitation is an important meteorological indicator that has a direct and significant impact on ecology, agriculture, hydrology, and other vital areas of human health and life. It is therefore essential to monitor variations of this parameter at a global and local scale. To monitor and predict long-term changes in climate elements, Global Circulation Models (GCMs) can provide simulated global-scale climatic processes. Due to the low spatial resolution of these models, downscaling methods are required to convert such large-scale information to regional-scale data for local applications. Among the downscaling methods, the Statistical DownScaling Model (SDSM) and the Artificial Neural Networks (ANNs) are widely used due to their low computational volume and suitable output. These models mainly require training data, and generally, the reanalysis data obtained from the National Center for Environmental Prediction (NCEP) and European Centre for Medium-range Weather Forecasts (ECMWF) are used for this purpose. With an optimal downscaling method, instead of applying the humidity indices extracted from ECMWF data, the outputs of the function-based tropospheric tomography technique obtained from the Global Navigation Satellite System (GNSS) will be used. The reconstructed function-based tropospheric data is then fed to the SDSM and ANN methods used for downscaling. The results of both methods indicate that the tomography can increase the accuracy of the downscaling process by about 20 mm in the wet months of the year. This corresponds to an average improvement of 38% with regard to the root mean square error (RMSE) of the monthly precipitation.
Classification of Southern Corn Rust Severity Based on Leaf-Level Hyperspectral Data Collected under Solar Illumination
Authors: Gao Jianmeng , Ding Mingliang , Sun Qiuyu , Dong Jiayu , Wang Huanyi , Ma Zhanhong
Published: May 2022

Maize is one of the most important crops in China, and it is under a serious, ever-increasing threat from southern corn rust (SCR). The identification of wheat rust based on hyperspectral data has been proved effective, but little research on detecting maize rust has been reported. In this study, full-range hyperspectral data (350~2500 nm) were collected under solar illumination, and spectra collected under solar illumination (SCUSI) were separated into several groups according to the disease severity, measuring height and leaf curvature (the smoothness of the leaf surface). Ten indices were selected as candidate indicators for SCR classification, and their sensitivities to the disease severity, measuring height and leaf curvature, were subjected to analysis of variance (ANOVA). The better-performing indices according to the ANOVA test were applied to a random forest classifier, and the classification results were evaluated by using a confusion matrix. The results indicate that the PRI was the optimal index for SCR classification based on the SCUSI, with an overall accuracy of 81.30% for mixed samples. The results lay the foundation for SCR detection in the incubation period and reveal potential for SCR detection based on UAV and satellite imageries, which may provide a rapid, timely and cost-effective detection method for SCR monitoring.
VPRNet: Virtual Points Registration Network for Partial-to-Partial Point Cloud Registration
Authors: Li Shikun , Ye Yang , Liu Jianya , Guo Liang
Published: May 2022

With the development of high-precision and high-frame-rate scanning technology, we can quickly obtain scan data of various large-scale scenes. As a manifestation of information fusion, point cloud registration is of great significance in various fields, such as medical imaging, autonomous driving, and 3D reconstruction. The Iterative Closest Point (ICP) algorithm, as the most classic algorithm, leverages the closest point to search corresponding points, which is the pioneer of correspondences-based approaches. Recently, some deep learning-based algorithms witnessed extracting deep features to compress point cloud information, then calculate corresponding points, and finally output the optimal rigid transformation like Deep Closest Point (DCP) and DeepVCP. However, the partiality of point clouds hinders the acquisition of enough corresponding points when dealing with the partial-to-partial registration problem. To this end, we propose Virtual Points Registration Network (VPRNet) for this intractable problem. We first design a self-supervised virtual point generation network (VPGnet), which utilizes the attention mechanism of Transformer and Self-Attention to fuse the geometric information of two partial point clouds, combined with the Generative Adversarial Network (GAN) structure to produce missing points. Subsequently, the following registration network structure is spliced to the end of VPGnet, thus estimating rich corresponding points. Unlike the existing methods, our network tries to eliminate the side effects of incompleteness on registration. Thus, our method expresses resilience to the initial rotation and sparsity. Various experiments indicate that our proposed algorithm shows advanced performance compared to recent deep learning-based and classical methods.
Snow Depth Measurements by GNSS-IR at an Automatic Weather Station, NUK-K
Authors: Dahl-Jensen Trine S. , Citterio Michele , Jakobsen Jakob , Ahlstrøm Andreas P. , Larson Kristine M. , Khan Shfaqat A.
Published: May 2022

Studies have shown that geodetic Global Navigation Satellite System (GNSS) stations can be used to measure snow depths using GNSS interferometric reflectometry (GNSS-IR). Here, we study the results from a customized GNSS setup installed in March through August 2020 at the Programme for Monitoring of the Greenland Ice Sheet (PROMICE) automatic weather station NUK-K located on a small glacier outside Nuuk, Greenland. The setup is not optimized for reflectometry purposes. The site is obstructed between 85 and 215 degrees, and as the power supply is limited due to the remote location, the logging time is limited to 3 h per day. We estimate reflector heights using GNSS-IR and compare the results to a sonic ranger also placed on the weather station. We find that the snow melt measured by GNSS-IR is comparable to the melt measured by the sonic ranger. We expect that a period of up to 45 cm difference between the two is likely related to the much larger footprint GNSS-IR and the topography of the area. The uncertainty on the GNSS-IR reflector heights increase from approximately 2 cm for a snow surface to approximately 5 cm for an ice surface. If reflector height during snow free periods are part of the objective of a similar setup, we suggest increasing the logging time to reduce the uncertainty on the daily estimates.
Above-Ground Biomass Estimation of Plantation with Different Tree Species Using Airborne LiDAR and Hyperspectral Data
Authors: Gao Linghan , Chai Guoqi , Zhang Xiaoli
Published: May 2022

Forest above-ground biomass (AGB) is an important index to evaluate forest carbon sequestration capacity, which is very important to maintain the stability of forest ecosystems. At present, the wide use of remote sensing technology makes it possible to estimate the large-scale forest AGB accurately and efficiently. Airborne hyperspectral remote sensing data can obtain rich spectral information and spatial structure information on the forest canopy with the characteristics of high spatial and hyperspectral resolution. Airborne LiDAR data can describe the three-dimensional structure characteristics of a forest and provide vertical structure information related to biomass. Based on the characteristics of the two data sources, this study takes Gaofeng forest farm in Nanning, Guangxi, as the study area, Chinese fir, pine tree, eucalyptus and other broadleaved trees as the research object, and constructs the AGB estimation models of different tree species by fusing airborne LiDAR and hyperspectral features. Firstly, spectral features, texture features, vegetation index, wavelet transform features and edge features are extracted from hyperspectral data. Canopy structure features, point cloud structure features, point cloud density features and terrain features are extracted from airborne LiDAR data. Secondly, the random forest (RF) method is used to screen the features of the two sets of data, and the features with the highest importance are selected. Finally, based on the optimal features of the two data sources, the forest AGB model is constructed using the multiple stepwise regression method. The results show that the texture features extracted by wavelet transform can be used for AGB modeling. The AGB of eucalyptus has high correlation with height features derived from airborne LiDAR, the AGB of other broadleaved trees mostly depends on the wavelet transform texture features from airborne hyperspectral data, while the AGB of Chinese fir and pine tree has high correlation with both height features and spectral features. Feature-fusion-based LiDAR and hyperspectral data can greatly improve the accuracy of the AGB models. The accuracy of the optimal AGB models of Chinese fir, pine tree, eucalyptus and other broadleaved trees is 0.78, 0.95, 0.72 and 0.89, respectively. In conclusion, more accurate estimation results can be obtained by combining active and passive remote sensing data for forest AGB estimation, which provides a solution for carbon storage assessment and forest ecosystem assessment.