bluuebunny/crossref_metadata_2025 huggingface dataset:
Nanobiochar and Copper Oxide Nanoparticles Mixture Synergistically Increases Soil Nutrient Availability and Improves Wheat Production
Authors: Rashid Muhammad Imtiaz , Shah Ghulam Abbas , Sadiq Maqsood , Amin Noor ul , Ali Arshid Mahmood , Ondrasek Gabrijel , Shahzad Khurram
Published: March 2023

Recently, nanomaterials have received considerable attention in the agricultural sector, due to their distinctive characteristics such as small size, high surface area to volume ratio, and charged surface. These properties allow nanomaterials to be utilized as nanofertilizers, that can improve crop nutrient management and reduce environmental nutrient losses. However, after soil application, metallic nanoparticles have been shown to be toxic to soil biota and their associated ecosystem services. The organic nature of nanobiochar (nanoB) may help to overcome this toxicity while maintaining all the beneficial effects of nanomaterials. We aimed to synthesize nanoB from goat manure and utilize it with CuO nanoparticles (nanoCu) to influence soil microbes, nutrient content, and wheat productivity. An X-ray diffractogram (XRD) confirmed nanoB synthesis (crystal size = 20 nm). The XRD spectrum showed a distinct carbon peak at 2θ = 42.9°. Fourier-transform spectroscopy of nanoB’s surface indicated the presence of C=O, C≡N–R, and C=C bonds, and other functional groups. The electron microscopic micrographs of nanoB showed cubical, pentagonal, needle, and spherical shapes. NanoB and nanoCu were applied alone and as a mixture at the rate of 1000 mg kg−1 soil, to pots where wheat crop was grown. NanoCu did not influence any soil or plant parameters except soil Cu content and plant Cu uptake. The soil and wheat Cu content in the nanoCu treatment were 146 and 91% higher, respectively, than in the control. NanoB increased microbial biomass N, mineral N, and plant available P by 57, 28, and 64%, respectively, compared to the control. The mixture of nanoB and nanoCu further increased these parameters, by 61, 18, and 38%, compared to nanoB or nanoCu alone. Consequently, wheat biological, grain yields, and N uptake were 35, 62 and 80% higher in the nanoB+nanoCu treatment compared to the control. NanoB further increased wheat Cu uptake by 37% in the nanoB+nanoCu treatment compared to the nanoCu alone. Hence, nanoB alone, or in a mixture with nanoCu, enhanced soil microbial activity, nutrient content, and wheat production. NanoB also increased wheat Cu uptake when mixed with nanoCu, a micronutrient essential for seed and chlorophyll production. Therefore, a mixture of nanobiochar and nanoCu would be recommended to farmers for improving their clayey loam soil quality and increasing Cu uptake and crop productivity in such agroecosystems.
Surface Engineering of Regenerated Cellulose Nanocomposite Films with High Strength, Ultraviolet Resistance, and a Hydrophobic Surface
Authors: Zhu Ying , Wang Tianhao , Dai Yanan , Wang Ye , Ding Yukun , Zhang Liping
Published: March 2023

Regenerated cellulose packaging materials can alleviate the environmental pollution and carbon emissions caused by conventional plastics and other chemicals. They require regenerated cellulose films with good barrier properties, such as strong water resistance. Herein, using an environmentally friendly solvent at room temperature, a straightforward procedure for synthesizing these regenerated cellulose (RC) films, with excellent barrier properties and doping with nano-SiO2, is presented. After the surface silanization modification, the obtained nanocomposite films exhibited a hydrophobic surface (HRC), in which the nano-SiO2 provided a high mechanical strength, whereas octadecyltrichlorosilane (OTS) provided hydrophobic long-chain alkanes. The contents of the nano-SiO2 and the concentrations of the OTS/n-hexane in regenerated cellulose composite films are crucial, as they define its morphological structure, tensile strength, UV-shielding ability, and the other performance of these composite films. When the nano-SiO2 content was 6%, the tensile stress of the composite film (RC6) increased by 41.2%, the maximum tensile stress was 77.22 MPa, and the strain-at-break was 14%. Meanwhile, the HRC films had more superior multifunctional integrations of tensile strength (73.91 MPa), hydrophobicity (HRC WCA = 143.8°), UV resistance (>95%), and oxygen barrier properties (5.41 × 10−11 mL·cm/m2·s·Pa) than the previously reported regenerated cellulose films in packaging materials. Moreover, the modified regenerated cellulose films could biodegrade entirely in soil. These results provide an experimental basis for preparing regenerated-cellulose-based nanocomposite films that exhibit a high performance in packaging applications.
RETRACTED: Shen et al. Investigation of the Ordered Structure in Partially Melted Isotactic Polypropylene. Polymers 2021, 13, 3354
Authors: Shen Junfang , Zhu Derong , An Junchao , Min Zhiyu , Chen Jingbo
Published: March 2023

The published article [...]
Photo- and Water-Degradation Phenomena of ZnO Bio-Blend Based on Poly(lactic acid) and Polyamide 11
Authors: Puglisi Roberta , Scamporrino Andrea Antonino , Dintcheva Nadka Tzankova , Filippone Giovanni , Bruno Elena , Scarfato Paola , Cerruti Pierfrancesco , Carroccio Sabrina Carola
Published: March 2023

The goal of this work was to investigate the morphological and chemical–physical changes induced by adding ZnO nanoparticles to bio-based polymeric materials based on polylactic acid (PLA) and polyamide 11 (PA11). Precisely, the photo- and water-degradation phenomena of nanocomposite materials were monitored. For this purpose, the formulation and characterization of novel bio-nanocomposite blends based on PLA and PA11 at a ratio of 70/30 wt.% filled with zinc oxide (ZnO) nanostructures at different percentages were performed. The effect of ZnO nanoparticles (≤2 wt.%) within the blends was thoroughly explored by employing thermogravimetry (TGA), size exclusion chromatography (SEC), matrix-assisted laser desorption ionization–time-of-flight mass spectrometry (MALDI-TOF MS) and scanning and transmission electron microscopy (SEM and TEM). Adding up to 1% wt. of ZnO resulted in a higher thermal stability of the PA11/PLA blends, with a decrement lower than 8% in terms of molar masses (MMs) values being obtained during blend processing at 200 °C. ZnO promoted trans-ester-amide reactions between the two polymers, leading to the formation of PLA/PA11 copolymers. These species could work as compatibilisers at the polymer interface, improving thermal and mechanical properties. However, the addition of higher quantities of ZnO affected such properties, influencing the photo-oxidative behaviour and thus thwarting the material’s application for packaging use. The PLA and blend formulations were subjected to natural aging in seawater for two weeks under natural light exposure. The 0.5% wt. ZnO sample induced polymer degradation with a decrease of 34% in the MMs compared to the neat samples.
Epoxy-Modified Bismaleimide Structural Adhesive Film Toughened Synergistically with PEK-C and Core–Shell Polymers for Bonding CFRP
Authors: Zhao Liwei , Xu Xin , Xiao Wanbao , Li Hongfeng , Feng Hao , Liu Changwei , Qiao Yingjie , Bai Xuefeng , Wang Dezhi , Qu Chunyan
Published: March 2023

Bismaleimide (BMI) resin-based structural adhesives have excellent heat resistance, with important applications demonstrated in the bonding of high-temperature BMI composites. In this paper, we report an epoxy-modified BMI structural adhesive with excellent properties for bonding BMI-based CFRP. We prepared the BMI adhesive using epoxy-modified BMI as the matrix and PEK-C and core–shell polymers as synergistic tougheners. We found that the epoxy resins improve the process and bonding properties of BMI resin but slightly reduce thermal stability. PEK-C and core–shell polymers synergistically improve the toughness and bonding performances of the modified BMI adhesive system and allow the maintenance of heat resistance. The optimized BMI adhesive exhibits excellent heat resistance, with a high glass transition temperature of 208.6 °C and a high thermal degradation temperature of 425.4 °C. Most importantly, the optimized BMI adhesive exhibits satisfactory intrinsic bonding and thermal stability. It has a high shear strength of 32.0 MPa at room temperature and up to 17.9 MPa at 200 °C. The BMI adhesive-bonded composite joint has a high shear strength of 38.6 and 17.3 MPa at room temperature and 200 °C, respectively, indicating effective bonding and excellent heat resistance.
Identification of Supramolecular Structures of Porphyrin Polymer on Single-Walled Carbon Nanotube Surface Using Microscopic Imaging Techniques
Authors: Abd El-Mageed Ahmed I. A. , Ogawa Takuji
Published: March 2023

Although the supramolecular structure of porphyrin polymers on flat surfaces (i.e., mica and HOPG) has been extensively studied, the self-assembly arrays of porphyrin polymers on the SWNT (as curved nanocarbon surfaces) have yet to be fully identified and/or investigated, especially using microscopic imaging techniques, i.e., scanning tunneling microscopy (STM), atomic force microscopy (AFM), and transmission electron microscopy (TEM). This study reports the identification of the supramolecular structure of poly-[5,15-bis-(3,5-isopentoxyphenyl)-10,20-bis ethynylporphyrinato]-zinc (II) on the SWNT surface using mainly AFM and HR-TEM microscopic imaging techniques. After synthesizing around >900 mer of porphyrin polymer (via Glaser-Hay coupling); the as-prepared porphyrin polymer is then non-covalently adsorbed on SWNT surface. Afterward, the resultant porphyrin/SWNT nanocomposite is then anchored with gold nanoparticles (AuNPs), which are used as a marker, via coordination bonding to produce a porphyrin polymer/AuNPs/SWNT hybrid. The polymer, AuNPs, nanocomposite, and/or nanohybrid are characterized using 1H-NMR, mass spectrometry, UV-visible spectroscopy, AFM, as well as HR-TEM measuring techniques. The self-assembly arrays of porphyrin polymers moieties (marked with AuNPs) prefer to form a coplanar well-ordered, regular, repeated array (rather than wrapping) between neighboring molecules along the polymer chain on the tube surface. This will help with further understanding, designing, and fabricating novel supramolecular architectonics of porphyrin/SWNT-based devices.
An Ant Colony Optimization-Simulated Annealing Algorithm for Solving a Multiload AGVs Workshop Scheduling Problem with Limited Buffer Capacity
Authors: Wang Zishi , Wu Yaohua
Published: March 2023

In this paper, we address a multiload AGVs workshop scheduling problem with limited buffer capacity. This has important theoretical research value and significance in the manufacturing field in considering the efficient multiload AGVs widely used today, and in the limited buffer area in production practice. To minimize the maximum completion time, an improved ant colony optimization-simulated annealing algorithm based on a multiattribute dispatching rule is proposed. First, we introduce a multiattribute dispatching rule, which combines two attributes, delivery completion time and input queue through dynamic weights that are determined by the information about the system, using the multiattribute dispatching rule to construct the initial solution. Then, with the ant colony optimization-simulated annealing algorithm as the basic framework, we propose a method for calculating transfer probability based on the multiattribute dispatching rule, which obtains heuristic information through the proposed rule. Further, we propose a path branch mechanism and dynamic equilibrium mechanism, aiming to efficiently construct the ant path and dynamically adjust ant path distribution. We propose a key job strategy and design a 2-opt neighborhood search method based on key jobs. Data experiments demonstrate the multiattribute dispatching rule is superior over other heuristic dispatching rules; the algorithm improvement strategies proposed are effective when used simultaneously or separately. Further, the proposed algorithm in this paper is superior over other heuristic algorithms and adapts to all kinds of instances.
Influence of Different Pre-Distillation Steps on Aromatic Profile of Plum Spirits Produced by Traditional and Modified Methods
Authors: Popović Branko , Mitrović Olga , Nikićević Ninoslav , Tešević Vele , Urošević Ivan , Miletić Nemanja , Milojević Svetomir
Published: March 2023

The aim of this study was to compare the aromatic profile of plum spirits, obtained from the Požegača and Stanley varieties, as affected by different combinations of pre-distillation steps used in traditional and six modified production methods that are common in Serbian distilleries. Traditional plum spirits (produced from spontaneously fermented mashes of crushed plums with stones distilled after two months of storage) had the highest contents of ethyl acetate, benzaldehyde, and total acids, which resulted in the occurrence of an unpleasant solvent-like and stone-like odour and acidic taste. These sensory defects were overcome by the distillation of fermented mashes immediately after the completion of alcoholic fermentation. Depending on the combination of the pre-distillation steps, plum spirits from mashes distilled immediately after alcoholic fermentation were characterized by different aromatic profiles: closer to traditional (from spontaneously fermented crushed plums with/without stones) or with a more pronounced fruity character (from pulped plums without stones regardless of the way of fermentation). These differences in aroma profiles have arisen mostly because of the significantly different contents and OAVs of ethyl esters and volatile fatty acids. The appropriate combination of the pre-distillation steps, which is adapted to the variety, can significantly improve the quality of the plum spirit compared to the traditionally produced spirit.
Polymer/Graphene Nanocomposites via 3D and 4D Printing—Design and Technical Potential
Authors: Kausar Ayesha , Ahmad Ishaq , Zhao Tingkai , Aldaghri O. , Eisa M. H.
Published: March 2023

Graphene is an important nanocarbon nanofiller for polymeric matrices. The polymer–graphene nanocomposites, obtained through facile fabrication methods, possess significant electrical–thermal–mechanical and physical properties for technical purposes. To overcome challenges of polymer–graphene nanocomposite processing and high performance, advanced fabrication strategies have been applied to design the next-generation materials–devices. This revolutionary review basically offers a fundamental sketch of graphene, polymer–graphene nanocomposite and three-dimensional (3D) and four-dimensional (4D) printing techniques. The main focus of the article is to portray the impact of 3D and 4D printing techniques in the field of polymer–graphene nanocomposites. Polymeric matrices, such as polyamide, polycaprolactone, polyethylene, poly(lactic acid), etc. with graphene, have been processed using 3D or 4D printing technologies. The 3D and 4D printing employ various cutting-edge processes and offer engineering opportunities to meet the manufacturing demands of the nanomaterials. The 3D printing methods used for graphene nanocomposites include direct ink writing, selective laser sintering, stereolithography, fused deposition modeling and other approaches. Thermally stable poly(lactic acid)–graphene oxide nanocomposites have been processed using a direct ink printing technique. The 3D-printed poly(methyl methacrylate)–graphene have been printed using stereolithography and additive manufacturing techniques. The printed poly(methyl methacrylate)–graphene nanocomposites revealed enhanced morphological, mechanical and biological properties. The polyethylene–graphene nanocomposites processed by fused diffusion modeling have superior thermal conductivity, strength, modulus and radiation- shielding features. The poly(lactic acid)–graphene nanocomposites have been processed using a number of 3D printing approaches, including fused deposition modeling, stereolithography, etc., resulting in unique honeycomb morphology, high surface temperature, surface resistivity, glass transition temperature and linear thermal coefficient. The 4D printing has been applied on acrylonitrile-butadiene-styrene, poly(lactic acid) and thermosetting matrices with graphene nanofiller. Stereolithography-based 4D-printed polymer–graphene nanomaterials have revealed complex shape-changing nanostructures having high resolution. These materials have high temperature stability and high performance for technical applications. Consequently, the 3D- or 4D-printed polymer–graphene nanocomposites revealed technical applications in high temperature relevance, photovoltaics, sensing, energy storage and other technical fields. In short, this paper has reviewed the background of 3D and 4D printing, graphene-based nanocomposite fabrication using 3D–4D printing, development in printing technologies and applications of 3D–4D printing.
Mathematical Modeling of Eicosanoid Metabolism in Macrophage Cells: Cybernetic Framework Combined with Novel Information-Theoretic Approaches
Authors: Aboulmouna Lina , Khanum Sana , Heidari Mohsen , Raja Rubesh , Gupta Shakti , Maurya Mano R. , Grama Ananth , Subramaniam Shankar , Ramkrishna Doraiswami
Published: March 2023

Cellular response to inflammatory stimuli leads to the production of eicosanoids—prostanoids (PRs) and leukotrienes (LTs)—and signaling molecules—cytokines and chemokines—by macrophages. Quantitative modeling of the inflammatory response is challenging owing to a lack of knowledge of the complex regulatory processes involved. Cybernetic models address these challenges by utilizing a well-defined cybernetic goal and optimizing a coarse-grained model toward this goal. We developed a cybernetic model to study arachidonic acid (AA) metabolism, which included two branches, PRs and LTs. We utilized a priori biological knowledge to define the branch-specific cybernetic goals for PR and LT branches as the maximization of TNFα and CCL2, respectively. We estimated the model parameters by fitting data from three experimental conditions. With these parameters, we were able to capture a novel fourth independent experimental condition as part of the model validation. The cybernetic model enhanced our understanding of enzyme dynamics by predicting their profiles. The success of the model implies that the cell regulates the synthesis and activity of the associated enzymes, through cybernetic control variables, to accomplish the chosen biological goal. The results indicated that the dominant metabolites are PGD2 (a PR) and LTB4 (an LT), aligning with their corresponding known prominent biological roles during inflammation. Using heuristic arguments, we also infer that eicosanoid overproduction can lead to increased secretion of cytokines/chemokines. This novel model integrates mechanistic knowledge, known biological understanding of signaling pathways, and data-driven methods to study the dynamics of eicosanoid metabolism.
Experimental Study on Cyclic Hydraulic Fracturing of Tight Sandstone under In-Situ Stress
Authors: Wu Xiaolong , Guo Yintong , Chang Xin , Bi Zhenhui , Zhao Guokai , Yang Hanzhi , Guo Wuhao
Published: March 2023

Sandstone oil–gas reservoirs in the Junggar Basin, China have great development potential. However, their ultra-deep formation depth leads to high crustal stress and high breakdown pressure. Therefore, in this research, we studied the cyclic hydraulic fracturing of tight sandstone with different combinations of “high-pressure duration + low-pressure duration” under high-stress conditions. Through laboratory experiments, the pump pressure curves, hydraulic fracture morphology, acoustic emission counts, and peak frequency of the samples were obtained. The results showed that: (1) Compared with conventional hydraulic fracturing, the breakdown pressure of cyclic hydraulic fracturing was reduced by more than 30%, the minimum threshold of cyclic pump pressure required for sample breakdown was between 60%Pb and 70%Pb, and cyclic hydraulic fracturing more easily formed complex and diverse hydraulic fractures. (2) In cyclic hydraulic fracturing, under the same upper limit of cyclic pump pressure, the shorter the high-pressure duration, the fewer the cycles required for sample breakdown. (3) Under the same “high-pressure duration + low-pressure duration” condition, the lower the upper limit of the cyclic pump pressure, and the greater the number of cycles required for sample breakdown. (4) The AE cumulative counts curves fluctuated greatly during cyclic hydraulic fracturing, rising in an obvious step-wise manner and the AE peak frequency was banded and mainly divided into three parts: low frequency, medium frequency, and high frequency.
Investigations on the Surface Integrity of Ti6Al4V under Modified Dielectric(s)-Based Electric Discharge Machining Using Cryogenically Treated Electrodes
Authors: Farooq Muhammad Umar , Anwar Saqib
Published: March 2023

The surface integrity of machined components is considered to be an important part of the quality matrix for high-performance applications in the aviation industry. Therefore, close attention is given to the components made up of hard-to-cut materials such as Ti6Al4V, which face processability challenges. In this regard, among the non-conventional machining processes, electric discharge machining is widely preferred for cutting Ti6Al4V. In this study, the potentiality of cryogenic-treated tool electrodes (graphite and aluminum) with unmodified (kerosene) and modified (kerosene with Span 20, Span 60, and Span 80) dielectrics are comprehensively investigated. A three-phased experimentation framework is deployed based on the following process parameters, i.e., surfactant type, surfactant concentration, electrode material, and pulse ON:OFF time. Thorough statistical analyses are performed based on the full factorial design of experiments, and the results are characterized by process physics. It is found that the cutting mechanism is highly dependent on the surfactants, especially their hydrophilic–lipophilic balance in the dielectric. The desirability-based process optimization results show that the unmodified process (with kerosene) produced relatively higher roughness values of 7.5 µm and 5.8 µm for aluminum and graphite electrodes, respectively. However, the modified process (with surfactant) resulted in a lower degree of roughness on the workpiece. The graphite electrode using S-60 with a resulting Ra of 1.73 µm outperformed the aluminum electrode using S-20, yielding an Ra of 3.4 µm. The S-60 surfactant resulted in minimum roughness on the workpiece with the fewest surface defects at the 25 g/L concentration, 50:25 µSec pulse ON:OFF time, and with the cryogenically treated graphite electrode.
Application of Plant Surfactants as Cleaning Agents in Shampoo Formulations
Authors: Bezerra Káren G. O. , Meira Hugo M. , Veras Bruno O. , Stamford Thayza C. M. , Fernandes Emanuel L. , Converti Attilio , Rufino Raquel D. , Sarubbo Leonie A.
Published: March 2023

With the increased demand for sustainable, hypoallergenic products, plant surfactants are a promising, eco-friendly option for cleaning products due to their low toxicity or even the absence of toxicity. In the present study, surfactant-rich extracts from Chenopodium quinoa, Glycine max, and Malpighia emarginata were assessed for their stability, antioxidant capacity, toxic potential, and cleaning potential in shampoo formulations. The surfactants in the extracts were isolated and characterized by NMR, UV-Vis, and FTIR spectroscopy. The results demonstrated that the extracts remained stable within the temperature and pH ranges tested. The antioxidant properties were also determined. In the analysis of irritation potential, G. max and C. quinoa exhibited low toxicity and no toxicity, respectively. The cleaning potential analysis confirmed that the extracts could be used as primary surfactants. Seven shampoo formulations were developed, which showed potential to reduce surface tension to the range of 27.1–31.7 mN/m and interfacial tension to the range of 5.4–7.3 mN/m. The wettability, percentage of solids, density, pH, and dirt dispersion of the formulas were within standard ranges, and the sebum removal capacity of the seven formulations was similar to or even better than that of a commercial shampoo.
A Gas Emission Prediction Model Based on Feature Selection and Improved Machine Learning
Authors: Shao Liangshan , Zhang Kun
Published: March 2023

This paper proposed a gas emission prediction method based on feature selection and improved machine learning, as traditional gas emission prediction models are neither accurate nor universally applicable. Through analysis, this paper identified 12 factors that affected gas emissions. A total of 30 groups of typical data for gas outflow were standardized, after which a full subset regression feature selection method was used to categorize 12 influencing factors into different regular patterns and select 18 feature parameter sets. Meanwhile, based on nuclear principal component analysis (KPCA), an optimized gas emission prediction model was constructed where the dimensionality of the original data was reduced. An optimized algorithm set was constructed based on the hybrid kernel extreme learning machine (HKELM) and the least squares support vector machine (LSSVM). The performance of feature parameters adopted in the prediction algorithm was evaluated according to certain metrics. By comparing the results of different sets, the final prediction sequence could be obtained, and a model that was composed of the optimal feature parameters was applied to the optimal machine learning algorithm. The results showed that the HKELM outperformed LSSVM in prediction accuracy, running speed, and stability. The root meant square error (RMSE) for the final prediction sequence was 0.22865, the determination coefficient (R2) was 0.99395, the mean absolute error (MAE) was 0.20306, and the mean absolute percentage error (MAPE) was 1.0595%. Every index of accuracy evaluation performed well and the constructed prediction model had high-prediction accuracy and a wide application.
Marginal Bone Loss and Treatment Complications with Mandibular Overdentures Retained by Two Immediate or Conventionally Loaded Implants—A Randomized Clinical Trial
Authors: Pardal-Peláez Beatriz , Dib Abraham , Guadilla Yasmina , Flores-Fraile Javier , Quispe-López Norberto , Montero Javier
Published: March 2023

This study aimed to assess marginal bone loss and complication rates of mandibular overdentures retained on two implants with conventional and immediate loading protocols. Twenty edentulous patients were treated with mandibular two-implant-retained overdentures and new complete maxillary dentures. In one half of the sample, the implants were loaded immediately by VulkanLoc® abutments. In the counterpart group, these abutments were connected to the implants two months after implant placement (conventional protocol). Treatment outcomes were evaluated at 2, 6, and 12 months after implant placement. According to the pre- and post-insertion radiographs, there was a mean marginal bone loss of 0.25–0.59 mm (CI 95%) after 13.4 ± 2.1 months of follow-up. There were no significant differences between groups. The failure rate (percentage of implants failing per year) was slightly higher in the conventional loading group (14.0 ± 32.7%) than in the immediate loading group (8.3 ± 18.0%). The findings of the present study suggested that there were no differences in marginal bone loss observed at one year for immediately loaded implants (0.40–0.39 mm) versus conventionally loaded implants (0.44- 0.36 mm) placed for the retention of mandibular overdentures. There were no differences in primary and secondary stability of immediately loaded versus conventional implants; however, in the conventional loading group, stability increased significantly between implant placement compared at both 6 and 12 months post-placement.
Acculturation and Intercultural Learning of Missionaries, Their Families, and the Role of Women in the Christian Mission—A Review of Literature from 1954 to 2010
Authors: Arnold Maik
Published: March 2023

This literature review summarises a wide range of empirical and systematic studies published between 1954 and 2010, including anthropological, cultural, historical, psychological, and sociological perspectives still underrepresented in cross-cultural communication and competence. Missionaries’ adaptation and acculturation, as well as of their families to new social and cultural environments and during reintegration at home are characterised by stressful experiences such as critical life events, premature termination, and upcoming retirements. Other studies highlight that certain personality traits and an ability to cope with psychological stress can predict the effectiveness of a mission assignment, e.g., spiritual and organisational commitment and expectations. Additionally, the review brings to light different role orientations of missionary wives, the psychological well-being within marriage, and the role of women in the Christian mission. Eventually, all findings will be subject to critical analysis and be instrumental in providing future research perspectives.
Beyond Fixed Political Models of Religion–State Relations
Authors: Zahir Azim
Published: March 2023

Some of the dominant academic approaches to Muslim politics continue to assume the centrality of Islam on the question religion’s relationship to the state and the possibility of successful democracy in Muslim-majority states. On the one hand, based on findings from large N-surveys, some scholars have argued that most Muslims in many Muslim-majority states desire a political ‘third model’ that is neither secular nor theocratic. Instead, they want democracy and a public role for shari’a and Islam. However, this literature does not fully explain what such a third model would mean for certain individual rights in practice. It also assumes a normative position that tends to favour one or another version of ‘Islamic’ democracy. On the other hand, some other scholars have argued that one or another form of a secular Muslim democracy is possible. Both views assume that the reinterpretation of religious resources is crucial to achieve the desired ends. This ‘reformist Islam approach’ to Muslim politics does not seriously consider the implications of servicing Islam, even in its more reformist forms, for political ends. Through a combination of theoretical and normative arguments and in-depth interviews conducted in the Maldives, this article argues that the plurality of viewpoints and underlying reasonings for those viewpoints among ordinary people suggest the necessity to move ‘beyond Islam’. As such, an alternative discursive democratisation approach that considers this plurality and takes discourses more neutrally without privileging religious discourses can be more capacious. Instead of fixating on a particular model of the religion–state relationship and a particular type of discourse (e.g., reformist Islamic), a discursive democratisation approach points to democratic possibilities and how the religion–politics and religion–state nexuses may be shaped and reshaped through discourse contestations within public spheres in Muslim-majority states such as the Maldives.
Turning Religious Experience into Reality: The Spiritual Power of Himma
Authors: Lala Ismail
Published: March 2023

The extremely influential mystic, Muḥyī al-Dīn ibn ‘Arabī (d. 634/1240), believes that the most advanced gnostics are imbued with a special power that turns their religious experience into reality. This is the power of himma—the power of existentiation that elite gnostics derive from God’s absolute power of existentiation. Ibn ‘Arabī and his followers assert that this power, which is exercised by the gnostics through an intense and unremitting concentration, actually shapes and forms external phenomenal reality as long as the concentration of the gnostic persists. This paper explores the different types of himmas that can exist, what kind of reality they allow the gnostics to perceive, and what relationship the objects created by himma have with the gnostic who exercised this power.
Aerosol Optical Properties and Types over Southern Africa and Reunion Island Determined from Ground-Based and Satellite Observations over a 13-Year Period (2008–2021)
Authors: Ranaivombola Marion , Bègue Nelson , Bencherif Hassan , Millet Tristan , Sivakumar Venkataraman , Duflot Valentin , Baron Alexandre , Mbatha Nkanyiso , Piketh Stuart , Formenti Paola , Goloub Philippe
Published: March 2023

Fires occur seasonally in Southern Africa, from June to November, increasing tropospheric aerosol loading and triggering harmful consequences for the environment and human health. This study aims to examine 13 years of aerosol optical characteristics and types over Southern Africa and Reunion Island. Using AERONET sun photometers and MODIS observations, we found that a high aerosol optical depth and Angström exponent are associated with two predominant types of aerosols (biomass burning/urban industrial and mixed type) throughout the spring season. According to CALIOP observations, the major aerosol types with occurrence frequencies above 10% are polluted continental/smoke, polluted dust, and elevated smoke, whereas dust, clean continental, and dusty marine have occurrence frequencies below 1%. In comparison to other seasons, the vertical profiles of elevated smoke have different shapes in spring, with a seasonal shift in the peak altitude (from 3–4 km), when fire activity is at its maximum. At these altitudes, the northern regions presented occurrence frequencies of 32% on average, while lower values were found for the southern or farthest regions (<10–20% on average). The Lagrangian HYSPLIT model back-trajectories demonstrated eastward transport, with air masses from South America and the Atlantic Ocean that recirculate around the study sites. The aerosols are mainly derived from active biomass burning areas near the study sites and, to a lesser extent, from remote sources such as South America.
Unified Framework for Ship Detection in Multi-Frequency SAR Images: A Demonstration with COSMO-SkyMed, Sentinel-1, and SAOCOM Data
Authors: Del Prete Roberto , Graziano Maria Daniela , Renga Alfredo
Published: March 2023

In the framework of maritime surveillance, vessel detection techniques based on spaceborne synthetic aperture radar (SAR) images have promoted extensive applications for the effective understanding of unlawful activities at sea. This paper deals with this topic, presenting a novel approach that exploits a cascade application of a pre-screening algorithm and a discrimination phase. Pre-screening is based on a constant false alarm rate (CFAR) detector, whereas discrimination exploits sub-look analysis (SLA). For the first time, the method has been validated with experiments on multi-frequency (C-, X-, and L-band) SAR images, demonstrating a significant reduction of up to 40% in false alarms within highly congested scenarios, along with a notable enhancement of the receiving operating characteristic (ROC) curves. For future synergic exploitation of multiple SAR missions, the developed dataset, composed of Sentinel-1, SAOCOM, and COSMO-SkyMed images, is comprehensive, having images gathered over the same area with a short time lag (below 15 min). Finally, the diversified processing chains and the results for each mission product and scenario are discussed. Being the first dataset of single-look complex (SLC) SAR multi-frequency data, the present work intends to encourage additional investigation in this promising field of research.
Detection of Corona Faults in Switchgear by Using 1D-CNN, LSTM, and 1D-CNN-LSTM Methods
Authors: Mohammed Alsumaidaee Yaseen Ahmed , Yaw Chong Tak , Koh Siaw Paw , Tiong Sieh Kiong , Chen Chai Phing , Yusaf Talal , Abdalla Ahmed N , Ali Kharudin , Raj Avinash Ashwin
Published: March 2023

The damaging effects of corona faults have made them a major concern in metal-clad switchgear, requiring extreme caution during operation. Corona faults are also the primary cause of flashovers in medium-voltage metal-clad electrical equipment. The root cause of this issue is an electrical breakdown of the air due to electrical stress and poor air quality within the switchgear. Without proper preventative measures, a flashover can occur, resulting in serious harm to workers and equipment. As a result, detecting corona faults in switchgear and preventing electrical stress buildup in switches is critical. Recent years have seen the successful use of Deep Learning (DL) applications for corona and non-corona detection, owing to their autonomous feature learning capability. This paper systematically analyzes three deep learning techniques, namely 1D-CNN, LSTM, and 1D-CNN-LSTM hybrid models, to identify the most effective model for detecting corona faults. The hybrid 1D-CNN-LSTM model is deemed the best due to its high accuracy in both the time and frequency domains. This model analyzes the sound waves generated in switchgear to detect faults. The study examines model performance in both the time and frequency domains. In the time domain analysis (TDA), 1D-CNN achieved success rates of 98%, 98.4%, and 93.9%, while LSTM obtained success rates of 97.3%, 98.4%, and 92.4%. The most suitable model, the 1D-CNN-LSTM, achieved success rates of 99.3%, 98.4%, and 98.4% in differentiating corona and non-corona cases during training, validation, and testing. In the frequency domain analysis (FDA), 1D-CNN achieved success rates of 100%, 95.8%, and 95.8%, while LSTM obtained success rates of 100%, 100%, and 100%. The 1D-CNN-LSTM model achieved a 100%, 100%, and 100% success rate during training, validation, and testing. Hence, the developed algorithms achieved high performance in identifying corona faults in switchgear, particularly the 1D-CNN-LSTM model due to its accuracy in detecting corona faults in both the time and frequency domains.
Effective Removal of Methylene Blue by Mn3O4/NiO Nanocomposite under Visible Light
Authors: Majeed Komal , Ambreen Jaweria , Khan Saeed Ahmed , Muhammad Saz , Shah Aqeel Ahmed , Bhatti Muhammad Ali , Batool Syeda Sitwat , Farooq Muhammad , Shah Bukhari Syed Nizam Uddin , Chandio Ali Dad , Gilani Sadaf Jamal , Bin Jumah May Nasser
Published: March 2023

Wastewater treatment is indispensable as wastewater can lead to adverse health effects and deteriorate the quality of life on earth. Photocatalysis is a facile methodology to address this issue. In this study, nanocomposites (NCs) of manganese oxide (Mn3O4) and nickel oxide (NiO) were synthesized in different weight ratios via the solid-state reaction route. Structural properties, optical properties, surface morphology, and functional group analysis of the synthesized nanomaterials were conducted using X-ray diffraction (XRD), UV– Vis spectroscopy, scanning electron microscopy (SEM) along with energy-dispersive X-ray (EDX) analysis, and Fourier-transform infrared (FTIR) spectroscopy, respectively. The bandgap of the nanocomposite decreases significantly from 2.35 eV for the Mn3O4 NPs to 1.65 eV for the Mn3O4/NiO nanocomposite (NC). Moreover, adsorption studies followed by the photocatalytic performance of the Mn3O4/NiO NCs were evaluated to determine the removal of methylene blue (MB) dye from wastewater. The photocatalytic performance of the nanocomposite enhances as the ratio of Mn3O4 in the composite increases from one weight percentage to three weight percentage. The photocatalytic degradation efficiency was calculated to be 95%. The results show that the synthesized NCs could play an important role in photocatalytic wastewater purification and environmental remediation.
A Sparse Multiclass Motor Imagery EEG Classification Using 1D-ConvResNet
Authors: Gangapuram Harshini , Manian Vidya
Published: March 2023

Multiclass motor imagery classification is essential for brain–computer interface systems such as prosthetic arms. The compressive sensing of EEG helps classify brain signals in real-time, which is necessary for a BCI system. However, compressive sensing is limited, despite its flexibility and data efficiency, because of its sparsity and high computational cost in reconstructing signals. Although the constraint of sparsity in compressive sensing has been addressed through neural networks, its signal reconstruction remains slow, and the computational cost increases to classify the signals further. Therefore, we propose a 1D-Convolutional Residual Network that classifies EEG features in the compressed (sparse) domain without reconstructing the signal. First, we extract only wavelet features (energy and entropy) from raw EEG epochs to construct a dictionary. Next, we classify the given test EEG data based on the sparse representation of the dictionary. The proposed method is computationally inexpensive, fast, and has high classification accuracy as it uses a single feature to classify without preprocessing. The proposed method is trained, validated, and tested using multiclass motor imagery data of 109 subjects from the PhysioNet database. The results demonstrate that the proposed method outperforms state-of-the-art classifiers with 96.6% accuracy.
Murder on the VR Express: Studying the Impact of Thought Experiments at a Distance in Virtual Reality
Authors: Kissel Andrew , Rechowicz Krzysztof J. , Shull John B.
Published: March 2023

Hypothetical thought experiments allow researchers to gain insights into widespread moral intuitions and provide opportunities for individuals to explore their moral commitments. Previous thought experiment studies in virtual reality (VR) required participants to come to an on-site laboratory, which possibly restricted the study population, introduced an observer effect, and made internal reflection on the participants’ part more difficult. These shortcomings are particularly crucial today, as results from such studies are increasingly impacting the development of artificial intelligence systems, self-driving cars, and other technologies. This paper explores the viability of deploying thought experiments in commercially available in-home VR headsets. We conducted a study that presented the trolley problem, a life-and-death moral dilemma, through SideQuestVR, a third-party website and community that facilitates loading applications onto Oculus headsets. Thirty-three individuals were presented with one of two dilemmas: (1) a decision to save five lives at the cost of one life by pulling a switch and (2) a decision to save five lives at the cost of one life by pushing a person onto train tracks. The results were consistent with those of previous VR studies, suggesting that a “VR-at-a-distance” approach to thought experiments has a promising future while indicating lessons for future research.
The Effectiveness of Augmented Reality in Physical Sustainable Education on Learning Behaviour and Motivation
Authors: Liang Lin , Zhang Zhishang , Guo Jianlan
Published: March 2023

This research explores the integration of information technology into physical education and uses augmented reality (AR) as an auxiliary tool to explore the impact of this teaching mode on the learning motivation, knowledge, and learning behaviour of beginner runners. A pre- and post-test control group design is adopted in this study. The study participants were 56 students implemented into a 16-session football teaching course. Before the teaching was implemented, the Learning Motivation Scale, independent variables were different learning modes, while the dependent ones were the participants’ learning performances, including their learning outcomes and motives, as well as their skill learning behaviours. The findings of this research are as follows: first, the experimental group (using AR) achieves better learning outcomes for motor skills than the control group. The experimental group also experiences stronger learning motives and better motor skill performances than the control one. Finally, the experimental group has a more positive attitude towards using the teaching materials, and the materials are more acceptable to them in comparison to the control one. This research contribution uses the advantages of AR to adopt an innovative teaching model, which can be highly appealing and motivating for learner behaviour. In practice, it also solves the deficiencies in the integration of information technology into physical education at this stage.
Shear Behavior and Asperity Damage of 3D Rough Joints under CNS Boundary Conditions Based on CZM Simulation
Authors: Zhang Shubo , Zheng Xin , Wang Changsheng , Wang Gang
Published: March 2023

Although boundary conditions can significantly impact the shear behaviors and asperity damage evolution of jointed rocks, numerical studies on the damage of 3D rough rock joints under the constant normal stiffness (CNS) boundary condition have rarely been reported. In this work, the three-dimensional model of the irregular joint surface is established by using point cloud reconstruction technology. Based on the cohesive zone model (CZM), we simulate the shear behavior of three-dimensional rough rock joints under the CNS boundary condition, which is realized by using embedded spring elements implemented with a Python subroutine. We conducted laboratory direct shear tests under CNS boundary conditions. The agreement with the laboratory experimental results verifies the fidelity of the numerical method. Our results show that boundary conditions can significantly affect the shear behavior of rock joints, especially in the post-peak stage. Under the same initial normal stress, the peak shear stress and the number of microcracks in the asperities increase significantly with the increase of normal stiffness. The proportion of shear cracks positively correlates with the normal stiffness, indicating that the normal stiffness affects the joint failure mode. The damaged area and the volume of asperities increase with the increase of normal stiffness. Moreover, the distribution of shear-induced asperity loss becomes more nonuniform, and the loss of joint roughness increases rapidly and nonlinearly.
A Vulnerability Assessment Framework for Product-Service Systems Based on Variation Mode and Effect Analysis
Authors: Wang Hanfei , Mitake Yuya , Tsutsui Yusuke , Alfarisi Salman , Shimomura Yoshiki
Published: March 2023

In recent decades, the product-service system (PSS) has been spotlighted due to its innovation and sustainability. As a novel business system, PSS provides additional value for products through the addition of service, which effectively upgrades the traditional manufacturing industry. For realizing a successful PSS, a robust and reliable operation stage is extremely important for users to stay satisfied and loyal. Thus, designers need to ensure that this system is not sensitive to any influential perturbation. Namely, they must achieve the desensitization of PSS to vulnerability. However, the current PSS design field still does not provide an effective method to assess the vulnerability in the whole life stage of PSS. This would lead to less time for the PSS provider to respond to various events. Furthermore, the tremendous loss could be caused due to the immaturity of the system. Therefore, this research has developed a vulnerability assessment framework based on variation mode and effect analysis (VMEA) for PSS. This developed framework has the ability to identify the potential noise factors and assess their severity based on multiple steps of analysis. This method has proved its effectiveness through an application example, and it is also expected to enable PSS researchers to design a robust PSS.