bluuebunny/crossref_metadata_2025 huggingface dataset:
Effects of Climate Change and Drought Tolerance on Maize Growth
Authors: Kim Kyung-Hee , Lee Byung-Moo
Published: October 2023

Climate change is affecting all regions of the world with different climates, and the scale of damage is increasing due to the occurrence of various natural disasters. In particular, maize production is highly affected by abnormal climate events such as heat waves and droughts. Increasing temperatures can accelerate growth and shorten the growing season, potentially reducing productivity. Additionally, enhanced temperatures during the ripening period can accelerate the process, reducing crop yields. In addition, drought stress due to water deficit can greatly affect seedling formation, early plant growth, photosynthesis, reproductive growth, and yield, so proper water management is critical to maize growth. Maize, in particular, is tall and broad-leaved, so extreme drought stress at planting can cause leaves to curl and stunt growth. It is important to understand that severe drought can have a detrimental effect on the growth and reproduction of maize. In addition, high temperatures caused by drought stress can inhibit the induction of flowering in male flowers and cause factors that interfere with pollen development. It is therefore important to increase the productivity of all food crops, including maize, while maintaining them in the face of persistent drought caused by climate change. This requires a strategy to develop genetically modified crops and drought-tolerant maize that can effectively respond to climate change. The aim of this paper is to investigate the effects of climate change and drought tolerance on maize growth. We also reviewed molecular breeding techniques to develop drought-tolerant maize varieties in response to climate change.
Fertilization of Microbial Composts: A Technology for Improving Stress Resilience in Plants
Authors: Ahmed Temoor , Noman Muhammad , Qi Yetong , Shahid Muhammad , Hussain Sabir , Masood Hafiza Ayesha , Xu Lihui , Ali Hayssam M. , Negm Sally , El-Kott Attalla F. , Yao Yanlai , Qi Xingjiang , Li Bin
Published: October 2023

Microbial compost plays a crucial role in improving soil health, soil fertility, and plant biomass. These biofertilizers, based on microorganisms, offer numerous benefits such as enhanced nutrient acquisition (N, P, and K), production of hydrogen cyanide (HCN), and control of pathogens through induced systematic resistance. Additionally, they promote the production of phytohormones, siderophore, vitamins, protective enzymes, and antibiotics, further contributing to soil sustainability and optimal agricultural productivity. The escalating generation of organic waste from farm operations poses significant threats to the environment and soil fertility. Simultaneously, the excessive utilization of chemical fertilizers to achieve high crop yields results in detrimental impacts on soil structure and fertility. To address these challenges, a sustainable agriculture system that ensures enhanced soil fertility and minimal ecological impact is imperative. Microbial composts, developed by incorporating characterized plant-growth-promoting bacteria or fungal strains into compost derived from agricultural waste, offer a promising solution. These biofertilizers, with selected microbial strains capable of thriving in compost, offer an eco-friendly, cost-effective, and sustainable alternative for agricultural practices. In this review article, we explore the potential of microbial composts as a viable strategy for improving plant growth and environmental safety. By harnessing the benefits of microorganisms in compost, we can pave the way for sustainable agriculture and foster a healthier relationship between soil, plants, and the environment.
Chemical Characterization and Chemotaxonomic Significance of Essential Oil Constituents of Matricaria aurea Grown in Two Different Agro-Climatic Conditions
Authors: Khan Merajuddin , Khan Mujeeb , Alshareef Eman , Alaqeel Shatha Ibrahim , Alkhathlan Hamad Z.
Published: October 2023

A comprehensive study on chemical characterization of essential oil (EO) constituents of a rarely explored plant species (Matricaria aurea) of the Asteraceae family grown in Saudi Arabia and Jordan was carried out. Analyses were conducted employing gas chromatographic approaches such as GC-MS, GC-FID, and Co-GC, as well as RT, LRI determination, and database and literature comparisons, on two diverse stationary phase columns, which led to the identification of a total of 135 constituents from both EOs. Oxygenated sesquiterpenes were found to be the most predominant chemical class of Saudi M. aurea EOs, in which α-bisabolol (27.8%), γ-gurjunenepoxide (21.7%), (E, E)-α-farnesene (16.3%), and cis-spiroether (7.5%) were present as major components. In contrast, the most dominant chemical class of Jordanian M. aurea oil was found to be sesquiterpene hydrocarbons, where (E, E)-α-farnesene (50.2%), γ-gurjunenepoxide (8.5%), (E)-β-farnesene (8.1%), and (Z, E)-α-farnesene (4.4%) were detected as chief constituents. It is interesting to mention here that Saudi and Jordanian M. aurea EOs showed quite interesting chemical compositions and were found to have different chemotypes when compared to previously reported M. aurea EO compositions.
Comparison of Saturation Rules Used for Gyrokinetic Quasilinear Transport Modeling
Authors: Parker Scott E. , Haubrich Calder S. , Tirkas Stefan , Cai Qiheng , Chen Yang
Published: October 2023

Theory-based transport modeling has been widely successful and is built on the foundations of quasilinear theory. Specifically, the quasilinear expression of the flux can be used in combination with a saturation rule for the toroidal mode amplitude. Most transport models follow this approach. Saturation rules are heuristic and difficult to rigorously derive. We compare three common saturation rules using a fairly accurate quasilinear expression for the fluxes computed using local linear gyrokinetic simulation. We take plasma parameters from experimental H-mode profiles and magnetic equilibrium and include electrons, deuterium, and carbon species. We find that the various saturation rules provide qualitatively similar behavior. This may help to explain why the different theory-based transport models can all predict core tokamak profiles reasonably well. Comparisons with nonlinear local and global gyrokinetic simulations are discussed.
Introducing “MEW2” Software: A Tool to Analyze MQ-NMR Experiments for Elastomers
Authors: Salamanca Fernando M. , Zepeda-Rodríguez Zenen , Diñeiro Laura , Escrivá Marina M. , Herrero Rebeca , Navarro Rodrigo , Valentín Juan L.
Published: October 2023

Low-field time-domain proton Nuclear Magnetic Resonance (NMR) spectroscopy is an attractive and powerful tool for studying the structure and dynamics of elastomers. The existence of crosslinks and other topological constraints in rubber matrices (entanglements and filler–rubber interactions, among others) renders the fast segmental fluctuations of the polymeric chains non-isotropic, obtaining nonzero residual dipolar couplings, which is the main observable of MQ-NMR experiments. A new software, Multiple quantum nuclear magnetic resonance analyzer for Elastomeric Networks v2 (MEW2), provides a new tool to facilitate the study of the molecular structure of elastomeric materials. This program quantitatively analyzes two different sets of experimental data obtained in the same experiment, which are dominated by multiple-quantum coherence and polymer dynamics. The proper quantification of non-coupled network defects (dangling chain ends, loops, etc.) allows the analyzer to normalize the multiple quantum intensity, obtaining a build-up curve that contains the structural information without any influence from the rubber dynamics. Finally, it provides the spatial distribution of crosslinks using a fast Tikhonov regularization process based on a statistical criterion. As a general trend, this study provides an automatic solution to a tedious procedure of analysis, demonstrating a new tool that accelerates the calculations of network structure using 1H MQ-NMR low-field time-domain experiments for elastomeric compounds.
The Progress in the Application of Dissolving Microneedles in Biomedicine
Authors: Yu Xueqing , Zhao Jing , Fan Daidi
Published: October 2023

In recent years, microneedle technology has been widely used for the transdermal delivery of substances, showing improvements in drug delivery effects with the advantages of minimally invasive, painless, and convenient operation. With the development of nano- and electrochemical technology, different types of microneedles are increasingly being used in other biomedical fields. Recent research progress shows that dissolving microneedles have achieved remarkable results in the fields of dermatological treatment, disease diagnosis and monitoring, and vaccine delivery, and they have a wide range of application prospects in various biomedical fields, showing their great potential as a form of clinical treatment. This review mainly focuses on dissolving microneedles, summarizing the latest research progress in various biomedical fields, providing inspiration for the subsequent intelligent and commercial development of dissolving microneedles, and providing better solutions for clinical treatment.
Electrospinning of Magnetite–Polyacrylonitrile Composites for the Production of Oxygen Reduction Reaction Catalysts
Authors: Mamun Al , García-Mateos Francisco José , Sabantina Lilia , Klöcker Michaela , Diestelhorst Elise , Ruiz-Rosas Ramiro , Rosas Juana María , Rodríguez-Mirasol José , Blachowicz Tomasz , Cordero Tomás
Published: October 2023

In this study, electrospun carbon fiber electrodes were prepared by the carbonization of PAN–Fe3O4 electrospun fibers at 800 °C for their use as catalysts in the oxygen reduction reaction in an alkaline electrolyte. Magnetic nanofiber mats were fabricated using a needle-free electrospinning method by incorporating magnetic nanoparticles into a polymer solution. Electrochemical tests revealed that the oxygen reduction reaction (ORR) activity is optimized at an intermediate magnetite loading of 30% wt. These catalysts not only show better performance compared to their counterparts but also achieve high selectivity to water at low potentials. The onset and half-wave potentials of 0.92 and 0.76 V shown by these samples are only slightly behind those of the commercial Pt 20%-carbon black ORR catalyst. The obtained results point out that the electrospinning of PAN-Fe3O4 solutions allows the preparation of advanced N-Fe ORR catalysts in fibrillar morphology.
Enhancing Textile Water Repellency with Octadecyltrichlorosilane (OTS) and Hollow Silica Nanoparticles
Authors: Sheraz Mahshab , Choi Byul , Kim Juran
Published: October 2023

Superhydrophobic coatings have attracted substantial attention owing to their potential application in various industries. Conventional textiles used in daily life are prone to staining with water and household liquids, necessitating the development of water-repellent and stain-resistant coatings. In this study, we fabricated a highly water-repellent superhydrophobic PET fabric by using an eco-friendly water-based coating process. Fluorine-free octadecyltrichlorosilane (OTS) solutions with various wt.% of hollow silica (HS) nanoparticles were used to produce a superhydrophobic surface via a facile dip coating method. Our findings revealed that the incorporation of HS nanoparticles substantially increased the water contact angle, with higher concentrations resulting in enhanced water repellency and increased surface roughness. The treated fabrics had a remarkable water contact angle of 152.4° ± 0.8°, demonstrating their superhydrophobic fiber surface. In addition, the durability of these superhydrophobic properties was investigated via a laundry procedure, which showed that the fabrics maintained their water repellency even after 20 laundering cycles. EDX and XRD analyses confirmed that the morphological evaluations did not reveal any substantial structural alterations. Significantly, the fibers maintained their strength and durability throughout the testing, enduring only minor hollow SiO2 nanoparticle loss. This eco-friendly and cost-effective method holds great potential for application in apparel and other industries, offering an effective solution to resist water stains and improve performance in various contexts.
Effect of Torrefaction on the Physiochemical Characteristics and Pyrolysis of the Corn Stalk
Authors: Chen Lei , Chen Xiangqian , Zhao Yuxiao , Xie Xinping , Yang Shuangxia , Hua Dongliang , Wang Chuanlei , Li Tianjin
Published: October 2023

Torrefaction of biomass is one of the most promising pretreatment methods for deriving biofuels from biomass via thermochemical conversion processes. In this work, the changes in physicochemical properties and morphology features of the torrefied corn stalk, the changes in physicochemical properties and morphology features of the torrefied corn stalk were investigated. The results of this study showed that the elemental content and proximate analysis of the torrefied corn stalk significantly changed compared with those of the raw corn stalk. In particular, at 300 °C, the volatile content decreased to 41.79%, while the fixed carbon content and higher heating value increased to 42.22% and 21.31 MJ/kg, respectively. The H/C and O/C molar ratios of torrefied corn stalk at the 300 °C were drastically reduced to 0.99 and 0.27, respectively, which are similar to those of conventional coals in China. Numerous cracks and pores were observed in the sample surface of torrefied corn stalk at the torrefaction temperature range of 275 °C–300 °C, which could facilitate the potential application of the sample in the adsorption process and promote the release of gas products in pyrolysis. In the pyrolysis phase, the liquid products of the torrefied corn stalk decreased, but the H2/CO ratio and the lower heating value of the torrefied corn stalk increased compared with those of the raw corn stalk. This work paves a new strategy for the investigation of the effect of torrefaction on the physiochemical characteristics and pyrolysis of the corn stalk, highlighting the application potential in the conversion of biomass.
Mechanism and Influence of Dispersants on the Action of Polymer Flocculants Used in Slurry Separation
Authors: Ren Guoping , Zhang Jian , Feng Tugen , Liang Yu , Yin Yihao
Published: October 2023

The application of polymer flocculants plays a pivotal role in the slurry separation process of shields, and the dispersant used for treating cutter mud cakes can significantly impact the effectiveness of polymer flocculants, potentially leading to reduced efficiency in slurry separation. Experiments were conducted to select appropriate flocculants and investigate the influence of dispersants on flocculant effectiveness, aiming to assess the effect of flocculants and explore the relationships and mechanisms governing their influence. Changes in the patterns of slurry flocculation were revealed in terms of flocculation-driven precipitation and vacuum-filtration effects. The purpose of this article is to provide a reference for the field application of polymer flocculants in the shield field. The conclusions are as follows. Inorganic flocculants containing 0.5% polyaluminum chloride (PAC) exhibit the most effective flocculation, demonstrating strong charge neutralization action. Organic flocculants containing 0.1% cationic polyacrylamides (CPAM) exhibit the most effective flocculation, demonstrating strong bridging and net capture effects. The dispersant sodium hexametaphosphate (SHMP) can significantly weaken the charge-neutralizing action of flocculants and slightly enhance bridging and net capture effects. SHMP can impede the flocculation of slurry with PAC. For CPAM, SHMP can enhance the flocculation of slurry at a low mass fraction (0.1% and 0.3%), while SHMP can significantly hinder flocculation at a high mass fraction (0.5% and 1%). A low mass fraction of SHMP reduced slurry viscosity to 246.3 mPa.s and enhanced vacuum filtration, while a high mass fraction of SHMP increased slurry viscosity to 667.2 mPa.s and hindered vacuum filtration. In conclusion, while dispersants reduce the effectiveness of inorganic flocculants at any mass fraction, a small number of dispersants enhances the performance of organic flocculants; thus, the organic flocculant CPAM is recommended for slurry separation.
Noise Reduction Design Method and Validation of Unequal-Pitch Blade Fan for Traction Motor
Authors: Li Weiye , Yang Liu , Hu Ao , Wu Yuhe , Li Gangyan
Published: October 2023

The traction motor of trains is an essential component that generates the traction force, but it has a significant influence on the indoor and outdoor acoustic environment during the running condition. To enhance passenger comfort and bolster the environmental performance of trains, regulatory standards and specifications governing train noise have imposed elevated criteria on both tonal noise and the overall A-weighted sound pressure level emanating from traction motors. This paper proposes an aerodynamic noise optimization design method based on aerodynamic interference. The objective function of the optimization is defined as the blade-passing frequency (BPF) noise and the A-weighted overall sound pressure level of the traction motor fan. The simulated annealing algorithm is used to optimize the circumferential distribution of the blades. The optimized unevenly spaced blade configuration of the fan effectively reduces the BPF sound pressure level amplitude by 4.6 dBA and the overall A-weighted sound pressure level by 1.2 dBA. The calculation results agree well with the experimental results. The study reveals that unevenly spaced blades contribute to better noise reduction at lower rotational speeds. However, the effect diminishes at higher speeds. The relationship between noise reduction and blade count is nonlinear, suggesting an optimal count for specific speeds.
Investigation of the Influence of Formation Water on the Efficiency of CO2 Miscible Flooding at the Core Scale
Authors: Pi Yanfu , Su Zailai , Liu Li , Wang Yutong , Zhang Shuai , Li Zhihao , Zhou Yufeng
Published: October 2023

This study investigated the impact of formation water on the mass transfer between CO2 and crude oil in low-permeability reservoirs through CO2 miscible flooding. Formation water leads to water blocks, which affect the effectiveness of CO2 miscible flooding. Therefore, we studied the impact and mechanisms of formation water on the CO2-oil miscibility. The microscale interaction between formation water-CO2-core samples was investigated using CT scanning technology to analyze its influence on core permeability parameters. In addition, CO2 miscible flooding experiments were conducted using the core displacement method to determine the effects of formation water salinity and average water saturation on minimum miscibility pressure (MMP) and oil displacement efficiency. The CT scanning results indicate that high-salinity formation water leads to a decrease in the porosity and permeability of the core as well as pore and throat sizes under miscible pressure conditions. The experimental results of CO2 miscible flooding demonstrate that CO2-oil MMP decreases as the salinity of the formation water increases. Moreover, as the average water saturation in the core increases, the water block effect strengthens, resulting in an increase in MMP. The recovery factors of cores with average water saturations of 30%, 45%, and 60% are 89.8%, 88.6%, and 87.5%, respectively, indicating that the water block effect lowers the oil displacement efficiency and miscibility.
Numerical Model of the Critical Gas Velocity for Liquid Displacement from the Lower Section of an Upward-Sloping Pipe
Authors: Duan Jimiao , He Manqiu , Tao Jiali , Liu Huishu , Xu Shuo , Wang Jian , Guo Yang , Chen Yan
Published: October 2023

Mobile pipelines are the most efficient and reliable tools for transporting a large amount of oil over long distances in combat, emergency rescue and disaster relief situations. In the completion of oil transfer or pipeline maintenance, the oil in the pipe is usually displaced by air. In the process of evacuation, due to the influence of terrain, working conditions and gravity, the gradual deposition of oil from upward-sloping pipeline sections to low-lying parts of the pipeline occurs, resulting in the formation of fluid deposits, which results in the incomplete drainage of the pipeline, directly affecting the recovery efficiency of the pipeline. According to the theory of gas–liquid two-phase stratified flow, the tail flow of a liquid membrane in an upward-sloping pipeline is analyzed as part of the gas-carrying oil flow process in an upward-sloping pipeline in this paper. The gas superficial velocity, which is the minimum velocity that can carry the accumulated liquid in the pipeline, is called the critical gas velocity of the gas-carrying liquid. A gas-carrying oil critical gas velocity model in an upward-sloping pipeline was established, and the change law of the critical gas-phase velocity in the upward-sloping pipeline was analyzed under the conditions of different tile angles, initial oil layer thicknesses and pipeline diameters. It was found that the tile angle had the greatest influence on the gas-carrying oil flow in the upward-sloping pipe, and the initial retained oil thickness had less of an influence on the gas-carrying oil flow in the upward-sloping pipe. When the pipeline diameter was small, the flow of the gas-carrying oil in the upward-sloping pipe was greatly affected by the pipeline diameter, but when the pipeline diameter was larger, the influence of the diameter on the gas-carrying oil flow in the upward-sloping pipe decreased gradually. The model developed can provide a useful means for the analysis and containment of accumulated liquid.
Investigation of the Real Meaning of the Stability Index and Its Empirical Analysis
Authors: Shper Vladimir , Sheremetyeva Svetlana , Sitnikova Irina , Smelov Vladimir , Khunuzidi Elena , Klochkov Yury , Gazizulina Albina
Published: October 2023

Assessment of process stability is a key to ensuring the high quality of any product, service, activity, etc. The main tool for doing this is a Shewhart control chart. However, it becomes difficult to analyze hundreds or thousands of control charts at a time for some up-to-date complex processes. In order to solve this problem, various indicators of process stability have been recently proposed with the Stability Index (SI) being the latest one, and, in many opinions, the best one. We have thoroughly analyzed different suggestions and found many of them ambiguous and sometimes even harmful to practitioners. Some examples of possible problems with the SI are provided below. It is argued that abnormal values of the SI can be caused not only by process instability, but by non-homogeneity, non-randomness, nonnormality, and autocorrelation as well. It is proved that the SI can be helpful for practitioners as an index to attract primary attention to the process. A proposal to rename the SI and widen significantly its application is given. Finally, some ways that practitioners could use this index more effectively are discussed.
Poly(tetrasubstituted-aryl imidazole)s: A Way to Obtain Multi-Chromophore Materials with a Tunable Absorption/Emission Wavelength
Authors: Chauveau Edouard , Perrin Lara , Marestin Catherine , Mercier Régis
Published: October 2023

Some original poly(tetrasubstituted imidazole)s incorporating different units were synthesized and characterized. These materials were obtained via a cascade polycondensation process assisted by microwave irradiation that was developed by our team. This time, we integrated two well-known chromophore structures into the macromolecular backbone, which were benzothiadiazole (BTD) and diketopyrrolopyrrole (DKPP). These new polymers were fully characterized: their chemical structures were confirmed using NMR spectroscopy and their thermal, optical and electrochemical properties were investigated and compared with a reference polymer containing a phenyl spacer instead of the mentioned chromophore units. These materials were found to exhibit a large Stokes shift of up to 350 nm. Furthermore, a polymer presenting large absorption on the UV–visible range and an emission close to the near-infrared region was obtained by coupling the mentioned moieties. According to the established properties of this latter polymer, it presents a potential for applications in biological imaging or optoelectronic devices.
Untargeted LC-QTOF-MS Analysis of Metabolites Produced by Penicillium brevicompactum during the Bioconversion of Ganoderic Acid A
Authors: Naidoo Vizelle , Mavumengwana Vuyo , Tapfuma Kudzanai , Rasifudi Ndiwanga F. , Mekuto Lukhanyo
Published: October 2023

The repurposing of expired drugs through bioconversion remains one of the most crucial research milestones, as this practice reduces drug contamination while producing compounds of significance. The present study investigated the bioconversion of ganoderic acid A (GAA) using Penicillium brevicompactum over a period of 3, 6 and 9 days. The GAA intensity reduced from 22,099 cps on day 0 to 11,040, 4700 and 18,126 cps on day 3, 6 and 9, respectively, thus demonstrating the degradation of GAA over time. The produced metabolites that were recovered using ethyl acetate as a solvent were determined using LC-QTOF-MS. P. brevicompactum produced a variety of compounds in the absence of GAA, while in its presence, it was observed that P. brevicompactum was able to convert GAA and produced ganomastenol A/B/D, vitamin E succinate, and aminopregnane on day 3, while on day 6, armillaripin and ganolucidic acid A were produced. After 9 days of operation, vitamin E succinate, ganolucidic acid A and lucilactaene were produced. The present study is the first report on the ability of P. brevicompactum to bioconvert GAA. The identified metabolites have been established to possess bioactivity against various ailments, thus contributing to the discovery of new drugs.
Management of the Risk of Blue-Green Algae Blooms in the Iskar Dam for Drinking Water Quality of Sofia City
Authors: Aleksova Margita , Schneider Irina , Velisha Seniha , Prodanova Eya
Published: October 2023

The introduction of systems for ensuring quality and safe drinking water and risk management is the World Health Organization (WHO) good practice introduced as a legislative requirement for all water supply organizations (Directive EU 2020/2184) on the quality of water intended for human consumption. A specific object of this research is the implemented risk assessment and management system, part of the drinking water safety plan for Sofia city. The water supply system from the water source to the end user, operated by Sofiyska voda JSC and part of Veolia, was analyzed. The hazards and risk events were reviewed for each component of the system—the catchment, water source, supply water pipes, drinking water treatment plants (DWTPs) and distribution water network. The results of the risk evaluation show that the risk of an algal bloom falls from medium risk, with a value of 36 in 2018. This risk was new for the Iskar Dam—the main water source for Sofia city. The purpose of the current study is to analyze the risk of blue-green algae blooming and the potential release of toxins in the Iskar Dam. A data analysis of phytoplankton counts, temperature of the water in the dam, precipitation, algal diversity and quantity of microcystins for a period of three years shows that there is a low probability of algae blooming. The concentration of microcystin LR was below 0.6 µg/L and of microcystin YR was below 0.1 µg/L. The highest phytoplankton count was 70,000 cells/mL in 2018, and it decreased to 30,000 cells/mL in 2020. The impact of the risk of “blue-green algae blooms in the Iskar Dam” is assessed as moderate (3) and that has not changed between 2018 and 2022. The likelihood of occurrence of this risk decreased from possible (3) to unlikely (2) after risk reassessment, and the current control effectiveness changed from weakly controlled (4) in 2018 to well controlled (2) in 2022, because more risk management actions were included in Sofiyska voda JSC. The results of the risk evaluation show that the risk of an algal bloom falls into the low-risk category with a value of 12, after measures were considered and a reassessment. As a preventive measure for better management and risk minimization, it is necessary to continue monitoring the phytoplankton count, species composition, concentration of algae toxins (microcystin LR) and nutrients in raw water from the Iskar Dam. This research has added value to the global database for surface water sources intended for human consumption and is focuses on a potential problem, valid for agricultural as well as for urban territories rich in diffused sources of pollution. The specific risk evaluation and management steps could be used and adapted by other water supply companies.
Energy-Saving Triangle: Internalizing Islamic Ethical Values on Energy Saving in Integrative Learning
Authors: Rohmatulloh Rohmatulloh , Hasanah Aan , Sahlani Lalan , Zuhri M. Tajudin
Published: October 2023

This study focused on integrating energy-saving education within the realms of natural science and religious, aligning with Islamic environmental values. Specifically, the aim was to create a teaching framework for instilling energy-saving values in Islamic secondary schools, integrating with the boarding school system (pesantren) guided by Islamic ethical principles. This research employed a descriptive case study approach in two Islamic school locations within Bandung Regency. Qualitative data were collected and analyzed using NVivo 12. Initially, a rich picture was used to depict the program’s setting, identify issues, and assimilate energy-saving Islamic values. The result was the synthesis of a triangular model, illustrating the internalization of Islamic ethical values related to energy conservation across science, religious subjects, and daily school activities. This model serves as a viable solution, particularly for Asian countries such as Indonesia, where the education system intertwines religious and scientific education in their curriculum, fostering students’ ecological awareness. The findings emphasize the need for competent educational stakeholders capable of innovatively integrating religion and science, possessing a solid understanding of energy conservation, to effectively implement these programs.
From Zora Neale to Missionary Mary: Womanist Aesthetics of Faith and Freedom
Authors: Thomas Ada C. M.
Published: October 2023

In this essay, I discuss the art of Missionary Mary Proctor, a contemporary folk artist from Tallahassee, Florida, in the context of the literary aesthetics of the renowned twentieth-century anthropologist and writer Zora Neale Hurston. In comparing these Southern-born African American women artists, I argue that both are rooted in an aesthetic praxis deriving from their shared womanist ethics. My goal in this inquiry is to highlight the faith-based aesthetic traditions of African American women and reveal the manner in which discourses of freedom intertwine with literary and visual aesthetics and faith-based practices in African American folk art and literature. To that end, I analyze the prevalence of themes of liberation within the spiritual discourses of Southern African American women artists such as Missionary Mary Proctor and theorize the manner in which a landscape of Black female liberation is envisioned within their works.
Neural Network Mapping of Industrial Robots’ Task Times for Real-Time Process Optimization
Authors: Righettini Paolo , Strada Roberto , Cortinovis Filippo
Published: October 2023

The ability to predict the maximal performance of an industrial robot executing non-deterministic tasks can improve process productivity through time-based planning and scheduling strategies. These strategies require the configuration and the comparison of a large number of tasks in real time for making a decision; therefore, an efficient task execution time estimation method is required. In this work, we propose the use of neural network models to approximate the task time function of a generic multi-DOF robot; the models are trained using data obtained from sophisticated motion planning algorithms that optimize the shape of the trajectory and the executed motion law, taking into account the kinematic and dynamic model of the robot. For scheduling purposes, we propose to evaluate only the neural network models, thus confining the online use of the motion planning software to the full definition of the actually scheduled task. The proposed neural network model presents a uniform interface and an implementation procedure that is easily adaptable to generic robots and tasks. The paper’s results show that the models are accurate and more efficient than the full planning pipeline, having evaluation times compatible with real-time process optimization.
Spatiotemporal Fusion Model of Remote Sensing Images Combining Single-Band and Multi-Band Prediction
Authors: Wang Zhiyuan , Fang Shuai , Zhang Jing
Published: October 2023

In recent years, convolutional neural network (CNN)-based spatiotemporal fusion (STF) models for remote sensing images have made significant progress. However, existing STF models may suffer from two main drawbacks. Firstly, multi-band prediction often generates a hybrid feature representation that includes information from all bands. This blending of features can lead to the loss or blurring of high-frequency details, making it challenging to reconstruct multi-spectral remote sensing images with significant spectral differences between bands. Another challenge in many STF models is the limited preservation of spectral information during 2D convolution operations. Combining all input channels’ convolution results into a single-channel output feature map can lead to the degradation of spectral dimension information. To address these issues and to strike a balance between avoiding hybrid features and fully utilizing spectral information, we propose a remote sensing image STF model that combines single-band and multi-band prediction (SMSTFM). The SMSTFM initially performs single-band prediction, generating separate predicted images for each band, which are then stacked together to form a preliminary fused image. Subsequently, the multi-band prediction module leverages the spectral dimension information of the input images to further enhance the preliminary predictions. We employ the modern ConvNeXt convolutional module as the primary feature extraction component. During the multi-band prediction phase, we enhance the spatial and channel information captures by replacing the 2D convolutions within ConvNeXt with 3D convolutions. In the experimental section, we evaluate our proposed algorithm on two public datasets with 16x resolution differences and one dataset with a 3x resolution difference. The results demonstrate that our SMSTFM achieves state-of-the-art performance on these datasets and is proven effective and reasonable through ablation studies.
Multiple Linear Regression and Machine Learning for Predicting the Drinking Water Quality Index in Al-Seine Lake
Authors: Jafar Raed , Awad Adel , Hatem Iyad , Jafar Kamel , Awad Edmond , Shahrour Isam
Published: October 2023

Ensuring safe and clean drinking water for communities is crucial, and necessitates effective tools to monitor and predict water quality due to challenges from population growth, industrial activities, and environmental pollution. This paper evaluates the performance of multiple linear regression (MLR) and nineteen machine learning (ML) models, including algorithms based on regression, decision tree, and boosting. Models include linear regression (LR), least angle regression (LAR), Bayesian ridge chain (BR), ridge regression (Ridge), k-nearest neighbor regression (K-NN), extra tree regression (ET), and extreme gradient boosting (XGBoost). The research’s objective is to estimate the surface water quality of Al-Seine Lake in Lattakia governorate using the MLR and ML models. We used water quality data from the drinking water lake of Lattakia City, Syria, during years 2021–2022 to determine the water quality index (WQI). The predictive performance of both the MLR and ML models was evaluated using statistical methods such as the coefficient of determination (R2) and the root mean square error (RMSE) to estimate their efficiency. The results indicated that the MLR model and three of the ML models, namely linear regression (LR), least angle regression (LAR), and Bayesian ridge chain (BR), performed well in predicting the WQI. The MLR model had an R2 of 0.999 and an RMSE of 0.149, while the three ML models had an R2 of 1.0 and an RMSE of approximately 0.0. These results support using both MLR and ML models for predicting the WQI with very high accuracy, which will contribute to improving water quality management.
The Role of Family and Media Environment on Aggressive Behaviour in Bulgarian Schools
Authors: Zografova Yolanda , Dimitrova Ekaterina Evtimova
Published: October 2023

The article examines the influence of two of the main social environments on students’ aggressive behaviours. On the one hand, attention is paid to the general socio-psychological climate in the family environment and the attitude of the parents towards the child; and on the other hand, a less frequently studied aspect related to aggressive manifestations of the children and adolescents towards the parents is addressed. The study explores how watching TV shows and movies, as well as video games, in which aggression and violence predominate, is connected to the frequency and degree of manifestation of types of aggression in adolescents. The survey was conducted at the end of 2017 among 992 students in 18 primary schools, secondary schools, and vocational schools/high schools in six different cities in different regions of Bulgaria. A structured questionnaire for the study of aggression in school was designed and was intended for students. The results of the study generally show that the verbal aggression towards parents (insulting and shouting) is mostly associated with verbal aggression towards both teachers and classmates. Regarding the influence of TV shows and movies containing aggression, it was found that students who watched movies with military, fighting and bloody scenes demonstrated more frequent manifestations of verbal aggression, but the TV contents did not significantly influence the manifestations of indirect aggression and physical aggression. However, the frequency of playing video games with aggressive content has a significant effect on all investigated forms of aggression, with the strongest effect on physical aggression. Aggression in social networks is a significant factor that affects the frequency of manifestation of various forms of aggression. Students who bully others on social networks stand out as the most aggressive (verbally, physically, and indirectly).
Direct and Indirect Effects of Emotions towards Party Leaders on Voting: Evidence from the 2018 Andalusian Regional Election
Authors: Cazorla Martín Ángel , Ortega Carmen , Montabes Juan
Published: October 2023

Party leaders are increasingly relevant to voters’ choices in parliamentary systems. However, most studies addressing the electoral impact of leaders have largely ignored voters’ emotional responses to party leaders. Additionally, little is known about the effect of party leaders in subnational or regional elections. Using data from a specific election survey, this article examines the effect of emotions towards party leaders on regional voting. It assesses whether emotional responses to party leaders not only have direct effects, but whether they also have indirect effects through partisanship on voting. We found evidence that emotions towards party leaders have both direct and indirect effects through partisanship on vote choice.
The Lives of Third-Country National Migrant Youth in Europe: Between Perceived Vulnerabilities and Available Resources
Authors: Giuliani Cristina , Gilodi Amalia , Regalia Camillo , Skrobanek Jan , Nienaber Birte
Published: October 2023

The idea for this Special Issue emerged from the Editors’ collaboration on the framework of the European project MIMY: EMpowerment through liquid Integration of Migrant Youth in vulnerable conditions [...]
The Rating Scale Paradox: An Application to the Solvency 2 Framework
Authors: Giacomelli Jacopo
Published: October 2023

This work aims to identify the optimal rating scale for the rating system used by a credit insurance company subjected to the Solvency 2 regulatory framework. To do so, we apply and further develop a previously published result concerning the rating scale properties. The partition underlying a given rating scale must satisfy two needs of the rating model user: efficient information synthesis and stable semantics. Those needs cannot be addressed together in general. Nonetheless, it is possible to specify the partition as a linear combination of the two choices that meet one requirement each. We numerically show that, in general, the optimal combination is nontrivial under realistic assumptions and is mainly driven by the target return fixed by the company’s stakeholders and the debtors’ probability of default distribution.
Robotic Liver Resection: Report of Institutional First 100 Cases
Authors: Conticchio Maria , Delvecchio Antonella , Ferraro Valentina , Stasi Matteo , Casella Annachiara , Filippo Rosalinda , Tedeschi Michele , Fiorentino Alba , Memeo Riccardo
Published: October 2023

Backgrounds: Liver surgery has developed progressively during the last 10 years, especially in minimally invasive approaches. Robotic surgery seemed to overcome laparoscopic limitations with 3D visualization, the increased degrees of freedom given with Endowrist instruments, tremor filtering, better dexterity, and improved ergonomics for the surgeon. Methods: This work was a retrospective analysis of our first 100 robotic hepatectomies from March 2020 to July 2022. Patient demographics characteristics and intra- and postoperative outcomes were analyzed. Results: A total of 59 males and 41 females, with a median age of 68 years, underwent a robotic liver resection. The indications for robotic liver resections were malignant lesions in 86% of patients. Anatomical resection (AR) was undertaken in 27% of cases and non-anatomical resection (NAR) in 63% of cases. None of the patients were converted to the ‘open’ approach. Postoperative complications were as follows: 1% of biliary leakage, 5% of ascites, 6% of pulmonary infections, and 3% of other sites’ infections. CONCLUSIONS Our results showed the satisfactory experience of a tertiary HPB center with its first 100 robotic liver resections. The opportunity to make the robotic approach routinary provided global growth of a surgical team, improving the quality of patient outcomes.
Development of a Novel 3D Highly Porous Structure for TiO2 Immobilization and Application in As(III) Oxidation
Authors: Scherer Filho Julio A. , Marinho Belisa A. , Vignola Fabiola , Mazur Luciana P. , González Sergio Y. G. , da Silva Adriano , Ulson de Souza Antônio Augusto , Guelli Ulson de Souza Selene M. A.
Published: October 2023

One of the main drawbacks of the application of photocatalysis for wastewater treatment is the use of dispersed photocatalysts, which are difficult to remove from effluent after the treatment process and may pose additional toxicity to the receiving bodies. As an alternative, immobilized catalysts can be applied; however, this strategy can increase the difficulties in mass and photo transfer. This work presents the development of an inert and highly porous support for TiO2 immobilization. The produced materials have a high surface area and contribute to diminishing the difficulties in mass and phototransfer during photocatalysis. Different types of polymeric materials were tested as support, and a Taguchi experimental design with an L9 arrangement was used to optimize the immobilization process and evaluate the effect of TiO2 content and the use of bidding agents, ultrasound, and thermic treatment. The grey automotive polyurethane foam proved to be the best support, using 5.0% of TiO2 (wt.%) in the immobilization suspension with Triton X as the binding agent and heat treatment during immobilization. At the optimal conditions, it was possible to achieve total As(III) oxidation (below the analytical detection limit) in 240 min, with nearly 100% As(V) present in solution at the end of the reaction (almost no As adsorption on the catalyst surface). In addition, the catalytic bed was able to promote the As(III) complete oxidation in up to five consecutive cycles without significant leaching or deactivation of the immobilized TiO2.
Susceptibility Assessment of Landslides in the Loess Plateau Based on Machine Learning Models: A Case Study of Xining City
Authors: He Li , Wu Xiantan , He Zhengwei , Xue Dongjian , Luo Fang , Bai Wenqian , Kang Guichuan , Chen Xin , Zhang Yuxiang
Published: October 2023

Landslide susceptibility assessment can effectively predict the spatial distribution of potential landslides, which is of great significance in fields such as geological disaster prevention, urban planning, etc. Taking Xining City as an example, based on GF-2 remote sensing image data and combined with field survey data, this study delineated the spatial distribution range of developed landslides. Key factors controlling landslides were then extracted to establish a landslide susceptibility assessment index system. Based on this, the frequency ratio (FR), random forest (RF), support vector machine (SVM), and artificial neural network (ANN) models were applied to spatially predict landslide susceptibility with slope units as the basis. The main results are as follows: (1) The overall spatial distribution of landslide susceptibility classes in Xining City is consistent, but the differences between different landslide susceptibility classes are significant. (2) The high-susceptibility area predicted by the FR-RF model is the largest, accounting for 15.48% of the total study area. The prediction results of the FR-ANN and FR-SVM models are more similar, with high-susceptibility areas accounting for 13.96% and 12.97%, respectively. (3) The accuracy verification results show that all three coupled models have good spatial prediction capabilities in the study area. The order of landslide susceptibility prediction capabilities from high to low is FR-RF model > FR-ANN model > FR-SVM model. This indicates that in the study area, the FR-RF model is more suitable for carrying out landslide susceptibility assessment.