bluuebunny/crossref_metadata_2025 huggingface dataset:
Chitosan Nanoparticles for Gastroesophageal Reflux Disease Treatment
Authors: Herdiana Yedi
Published: August 2023

Gastroesophageal Reflux Disease (GERD) is a chronic ailment that results from the backward flow of stomach acid into the esophagus, causing heartburn and acid regurgitation. This review explores nanotechnology as a novel treatment approach for GERD. Chitosan nanoparticles (CSNPs) offer several advantages, including biocompatibility, biodegradability, and targeted drug delivery capabilities. CSNPs have been extensively studied due to their ability to encapsulate and release medications in a controlled manner. Different nanoparticle (NP) delivery systems, including gels, microspheres, and coatings, have been developed to enhance drug retention, drug targeting, and controlled release in the esophagus. These nanoparticles can target specific molecular pathways associated with acid regulation, esophageal tissue protection, and inflammation modulation. However, the optimization of nanoparticle formulations faces challenges, including ensuring stability, scalability, and regulatory compliance. The future may see CSNPs combined with other treatments like proton pump inhibitors (PPIs) or mucosal protectants for a synergistic therapeutic approach. Thus, CSNPs provide exciting opportunities for novel GERD treatment strategies.
Synthesis and Comparative Study of Polyether-b-polybutadiene-b-polyether Triblock Copolymers for Use as Polyurethanes
Authors: Bi Pengzhi , Zhu Xiuzhong , Han Jinbang , Tian Li , Zhang Wanbin
Published: August 2023

In this paper, the effects of HTPBs with different main-chain microstructures on their triblock copolymers and polyurethane properties were investigated. Three polyether-modified HTPB triblock copolymers were successfully synthesized via a cationic ring-opening copolymerization reaction using three HTPBs with different microstructures prepared via three different polymerization methods as the macromolecular chain transfer agents and tetrahydrofuran (THF) and propylene oxide (PO) as the copolymerization monomers. Finally, the corresponding polyurethane elastomers were prepared using the three triblock copolymers as soft segments and toluene diisocyanate (TDI) as hard segments. The results of an analysis of the triblock copolymers showed that the triblock copolymers had lower viscosity and glass transition temperature (Tg) values as the HTPB 1,2 structure content decreased, although the effect on the thermal decomposition temperature was not significant. An analysis of the polyurethane elastomers revealed that as the content of the 1,2 structure in HTPB increased, its corresponding polyurethane elastomers showed a gradual increase in breaking strength and a gradual decrease in elongation at break. In addition, PU-1 had stronger crystallization properties compared to PU-2 and PU-3. However, the differences in the microstructures of the HTPBs did not seem to have much effect on the surface properties of the polyurethane elastomers.
Reactive Blending of Modified Thermoplastic Starch Chlorhexidine Gluconate and Poly(butylene succinate) Blending with Epoxy Compatibilizer
Authors: Thajai Nanthicha , Rachtanapun Pornchai , Thanakkasaranee Sarinthip , Punyodom Winita , Worajittiphon Patnarin , Phimolsiripol Yuthana , Leksawasdi Noppol , Ross Sukunya , Jantrawut Pensak , Jantanasakulwong Kittisak
Published: August 2023

Biodegradable starch-based polymers were developed by melt-blending modified thermoplastic starch (MTPS) with poly(butylene succinate) (PBS) blended with epoxy resin (Er). A modified thermoplastic starch blend with chlorhexidine gluconate (MTPSCh) was prepared by melt-blending cassava starch with glycerol and chlorhexidine gluconate (CHG) 1.0% wt. The Er was melt-blended with PBS (PBSE) at concentrations of 0.50%, 1.0%, 2.5%, and 5.0% (wt%/wt%). The mechanical properties, water resistance, and morphology of the MTPSCh/PBSE blends were investigated. The MTPSCh/PBSE2.5% blend showed an improvement in tensile strength (8.1 MPa) and elongation at break (86%) compared to the TPSCh/PBS blend (2.6 MPa and 53%, respectively). In addition, water contact angle measurements indicated an increase in the hydrophobicity of the MTPSCh/PBSE blends. Thermogravimetric analysis showed an improvement in thermal stability when PBS was added to the MTPSCh blends. Fourier transform infrared spectroscopy data confirmed a new reaction between the amino groups of CHG in MTPSCh and the epoxy groups of Er in PBSE, which improved the interfacial adhesion of the MTPSCh/PBSE blends. This reaction improved the mechanical properties, water resistance, morphology, and thermal stability of the TPSCh/PBSE blends.
Construction of a Bis(benzene sulfonyl)imide-Based Single-ion Polymer Artificial Layer for a Steady Lithium Metal Anode
Authors: Wang Yujie , Zhao Mengmeng , Chen Yazhou , Bao Haifeng , Li Chen
Published: August 2023

Dendrite growth and parasitic reactions with liquid electrolyte are the two key factors that restrict the practical application of the lithium metal anode. Herein, a bis(benzene sulfonyl)imide based single-ion polymer artificial layer for a lithium metal anode is successfully constructed, which is prepared via blending the as-prepared copolymer of lithiated 4, 4′-dicarboxyl bis(benzene sulfonyl)imide and 4,4′-diaminodiphenyl ether on the surface of lithium foil. This single-ion polymer artificial layer enables compact structure with unique continuous aggregated Li+ clusters, thus reducing the direct contact between lithium metal and electrolyte simultaneously, ensuring Li+ transport is fast and homogeneous. Based on which, the coulombic efficiency of the Li|Cu half-cell is effectively improved, and the cycle stability of the Li|Li symmetric cell can be prolonged from 160 h to 240 h. Surficial morphology and elemental valence analysis confirm that the bis(benzene sulfonyl)imide based single-ion polymer artificial layer effectively facilitates the Li+ uniform deposition and suppresses parasitic reactions between lithium metal anode and liquid electrolyte in the LFP|Li full-cell. This strategy provides a new perspective to achieve a steady lithium metal anode, which can be a promising candidate in practical applications.
Earthworm (Perionyx excavatus) Protein Hydrolysate: Hypoglycemic Activity and Its Stability for the Hydrolysate and Its Peptide Fractions
Authors: Bui Phong T. , Pham Khoa T. , Vo Tam D. L.
Published: August 2023

This study aims at exploring earthworm protein hydrolysate and its peptide fractions as a potential hypoglycemic agent by inhibiting α-amylase and α-glucosidase. Firstly, the best hydrolysis conditions to gain the hydrolysates with the highest α-amylase inhibitory activity (α-AIA) and α-glucosidase inhibitory activity (α-GIA) were figured out using a one-factor test. Next, the stability of the hypoglycemic activity of the hydrolysates and their 5 peptide fractions recovered using ultrafiltration membranes were assessed by employing the tests of in vitro digestion, thermal, and pH treatment. The results showed that at the best hydrolysis conditions, the hydrolysates exhibited α-AIA of 91.30 ± 2.51% and α-GIA of 44.69 ± 0.47%. Specifically, the <1 kDa peptide fraction from the hydrolysate expressed a greater α-AIA than that of acarbose, with nearly the same α-GIA as that of voglibose. The α-AIA and α-GIA of the hydrolysates and their fractions were enhanced after the in vitro digestion treatment, whereas they remained over 40% after the pH treatment in the range of 1 to 11 or heat treatment at 100 °C for 180 min. These data provide the preliminary evidence to develop the earthworm protein hydrolysate and its peptide fractions in functional food or nutraceutical products with hypoglycemic activity.
Research on the Evaluation of Emergency Management Synergy Capability of Coal Mines Based on the Entropy Weight Matter-Element Extension Model
Authors: Sun Chaolun , Hao Yu , Wei Jianping , Zhang Lijun
Published: August 2023

Emergency management synergy capability is not only a “touchstone” to measure the operation effect of the emergency system of coal mine enterprises, it is an important symbol to reflect its level. In order to improve the level of emergency management in coal mines based on the PPRR theory of crisis management cycle, in this paper a hierarchical evaluation index system is constructed based on the emergency management process. A quantitative evaluation model of emergency synergy capacity is proposes based on the entropy–weighted elemental topology method to conduct evaluation and model validation for the case of J coal mine in Henan Province. The results show that the overall evaluation of the emergency management synergy capability of J Coal Mine is at a “good” level, with the emergency prevention synergy capability, emergency preparedness synergy capability, and recovery and reconstruction synergy capability at a “good” level and the emergency response synergy capability is at a “average” level. This indicates that the evaluation model is consistent with the current development of coal mining enterprises and has universal applicability. Therefore, this research can provide decision-making support for emergency management synergistic capacity building of coal mining enterprises to enhance the inherent driving force behind the early completion of the dual carbon task in the coal mining industry.
Performance of Regenerated Activated Carbons on Pesticides Removal from the Aqueous Phase
Authors: Cansado Isabel Pestana da Paixão , Mourão Paulo Alexandre Mira , Castanheiro José Eduardo dos Santos Félix
Published: August 2023

Adsorbents presenting high adsorption capacity, fast adsorption rate, easy regeneration, and a good possibility for reusability are ideal for removing 4-chloro-2-methyl-phenoxyacetic acid (MCPA) or other pesticides from wastewater. Here, the effects of regeneration treatments on adsorption–desorption cycles are examined using two commercial activated carbons (ACs) (Merck and Norit 1240 X). MCPA adsorption was fast on Merck and Norit ACs in powder form (6 h) but on Norit AC, in granular form, adsorption was too slow, and the equilibrium time was reached only after 288 h. MCPA adsorption kinetic data were analyzed by applying pseudo-first-order, pseudo-second-order, and Weber–Morris models. The pseudo-second-order model fit better to all data, and the Weber–Morris representation allows confirming that on Norit 1240 X, in granular form, the pore diffusion was the limiting factor concerning the MCPA adsorption. Merck and Norit 1240 X (in powder and granular form) ACs loaded with MCPA were submitted to different regeneration process by washing with distilled water, ethanol, HNO3, and NaOH solutions and washed with NaOH solutions or ethanol followed by a thermal treatment. The ACs regenerated with ethanol performed well in the subsequent adsorption–desorption cycles. All ACs had more than 99% desorbed MCPA after the first cycle of washing with ethanol. The washing with NaOH solution was less efficient. The regeneration process, consisting of washing the sample with a solution of NaOH and subsequent heating at 573 K, was very effective. After this regeneration procedure, the amount of MCPA adsorbed on Norit 1240 X AC was even higher than the amount adsorbed in the first adsorption cycle. At present, washing methods for adsorbent regeneration are not used at an industrial level. However, research for environmentally friendly regeneration methods is necessary to achieve the objectives of the circular economy.
Application of AFM on Identifying Mechanical Properties of Individual Minerals and Surface Properties of Crack with High Resolution in Shale
Authors: Cheng Shizhong , Sheng Mao , Xu Peng
Published: August 2023

Improving the resolution and accuracy of the mechanical properties of organic-rich shale is very important. The results can reveal the mechanical properties of shale from micro scale and serve as a guide for the design of hydraulic fracture optimization parameters. This study introduced an advanced technique to obtain the mechanical properties of shale with high resolution (58.6 nm/pixel) by combining SEM, EDS, and Atomic Force Microscopy (AFM). To locate the target area in SEM and AFM accurately, a positioning technique that uses special distributions of pyrite was established. AFM PeakForce QNM mode was selected due to its advantages at capturing topography and mechanical properties in material. Results illustrated the ability of AFM to obtain the mechanical properties (modulus) of individual mineral components in shale, the detailed topography of crack, and mechanical properties of minerals in a specific area. In particular, the mechanical properties of minerals around crack explained the layered distribution of minerals around the fractures, and the cracks developed in the clay mineral layer was detected. This article demonstrates the great potential application of AFM in shale.
The Impact of Solar Radiation at Different Colombian Thermal Floors on an Adsorption Refrigeration Cycle
Authors: Serrano-Florez Dario , Camargo Aduar J. , Gutierrez Gail , Bastidas-Barranco Marlon , Chica Edwin , Colorado Andres
Published: August 2023

The process of energy transition in Colombia has sparked an exploration into appropriate geographical areas for the utilization of solar energy. The country’s rugged terrain and significant climate variability pose challenges for implementing standardized technologies uniformly across all regions. Consequently, this study aims to develop and apply a mathematical model to characterize the performance of a solar adsorption cooling system under the environmental conditions found in six distinct Colombian cities, taking into account different thermal profiles and extreme weather periods such as the El Niño and La Niña phenomena. The selected mathematical model was simulated in these cities, considering ambient temperature and solar radiation variables over a twelve-month period during these extreme weather phenomena and an additional twelve-month period representative of a typical year with minimal influence from these phenomena. The results indicated that despite a lower coefficient of performance (COP) compared to the other cities, Riohacha demonstrated a greater number of ice production days owing to its high levels of solar radiation.
Encrypted Model Predictive Control of a Nonlinear Chemical Process Network
Authors: Kadakia Yash A. , Suryavanshi Atharva , Alnajdi Aisha , Abdullah Fahim , Christofides Panagiotis D.
Published: August 2023

This work focuses on developing and applying Encrypted Lyapunov-based Model Predictive Control (LMPC) in a nonlinear chemical process network for Ethylbenzene production. The network, governed by a nonlinear dynamic model, comprises two continuously stirred tank reactors that are connected in series and is simulated using Aspen Plus Dynamics. For enhancing system cybersecurity, the Paillier cryptosystem is employed for encryption–decryption operations in the communication channels between the sensor–controller and controller–actuator, establishing a secure network infrastructure. Cryptosystems generally require integer inputs, necessitating a quantization parameter d, for quantization of real-valued signals. We utilize the quantization parameter to quantize process measurements and control inputs before encryption. Through closed-loop simulations under the encrypted LMPC scheme, where the LMPC uses a first-principles nonlinear dynamical model, we examine the effect of the quantization parameter on the performance of the controller and the overall encryption to control the input calculation time. We illustrate that the impact of quantization can outweigh those of plant/model mismatch, showcasing this phenomenon through the implementation of a first-principles-based LMPC on an Aspen Plus Dynamics process model. Based on the findings, we propose a strategy to mitigate the quantization effect on controller performance while maintaining a manageable computational burden on the control input calculation time.
Optimisation Using Response Surface Methodology of Quality, Nutritional and Antioxidant Attributes of ‘Wichita’ Pecan Nuts Roasted by Microwaves
Authors: Mukwevho Priscilla L. , Kaseke Tafadzwa , Fawole Olaniyi A.
Published: August 2023

Pecan (Carya illinoinensis) nuts are rich in functional compounds (unsaturated fatty acids, phytosterols, polyphenols, and tocopherols) associated with various health benefits. Commercially, pecan nuts are roasted to enhance their physical, chemical, and sensory properties. In the present study, response surface methodology (RSM) was used to optimise the quality and nutritional and antioxidant attributes of ‘Wichita’ pecan nuts roasted by using a microwave process with a range of microwave power (96.45–803.55 W) and roasting time (1.37–5.62 min). The microwave-roasted pecan nuts were analysed for hardness, total colour difference (TCD), and radical scavenging activity and modelled using the central composite design. The results showed that microwave power and roasting time significantly (p < 0.05) influenced the quality attributes of the pecan. The quadratic model adequately described the changes in TCD and hardness, respectively, while the 2FI model adequately described the changes in DPPH radical scavenging activity. To obtain the desired pecan nuts quality attributes (TCD = 1863.391; hardness = 28.755 N and DPPH radical scavenging activity = 33.877 mmol Trolox/g), the determined conditions were 700 W and 2.24 min, with a desirability of 0.557. The primary unsaturated fatty acids, including cis-oleic, cis-linoleic, α-linolenic, and stearic acids, were not affected (p < 0.05) by microwave roasting the pecan nuts at determined conditions. Volatile compounds, such as alcohols, aldehydes, ketones, lactones, hydrocarbons, and carboxylic acids, were identified in both raw and microwave-roasted pecan nuts, with limonene, which possesses various health properties, being the major volatile compound. It can be concluded that microwave roasting may be optimised using response surface methodology to produce quality pecan nuts that can be used as snacks or as an ingredient in other snack products.
Frac-Hit Prevention Countermeasures in Shale Gas Reservoirs with Natural Fractures
Authors: Xu Hualei , Jiang Houshun , Wang Jie , Wang Ting , Zhao Kangjia , Zhang Liangjun
Published: August 2023

The development of natural fractures (NFs) in shale gas reservoirs is conducive to improving the productivity of shale gas wells. However, NF development leads to high-frequency frac hits between the infill and parent wells, which critically restricts its efficiency. To elucidate the large contribution of hydraulic fractures (HFs) and NFs in frac hits during the production and the development of NF-developed shale gas reservoirs, such reservoirs in the WY area of western China are taken as an example. A total of 197 frac hits well events in this area are systematically classified via the frac-hit discrimination method, and the effects of different factors on HF- and NF- dominated frac hits are classified and studied. Combined with the correlation analysis method and the chart method, the main controlling factors affecting the two types of frac hits are determined, and the corresponding frac-hit prevention countermeasures are proposed. The research demonstrates that (1) the distribution and development of NFs are crucial to production after frac hits. NFs and HFs in the WY area cause 51% and 49%, respectively, of the frac hits. (2) The main controlling factors in NF-dominated frac hits are the approximation angle, fracture linear density, and horizontal stress difference, whereas they are net pressure in fractures, horizontal stress difference, and liquid strength in HF-dominated frac hits. Sensitivity analysis shows that the NF activation difficulty coefficient fluctuates between −35.1% and 47.6%, and the maximum hydraulic fracture length fluctuates between −43.5% and 25.29%. (3) The corresponding frac-hit prevention countermeasures are proposed for the two types of formation mechanisms from different approaches, including frac-hit risk assessment and path planning, production well pressurization and stress diversion, and infill-well fracturing parameter optimization. This paper not only provides a reference for exploring the formation mechanism of frac hits in fractured shale gas reservoirs but also a theoretical basis for the corresponding frac-hit prevention countermeasures.
Multiscale CFD Simulation of Multiphase Erosion Process in a Connecting Pipe of Industrial Polycrystalline Silicon Unit
Authors: Chen Sheng , Shi Jiarui , Yuan Jun , He Meng , Li Yongquan , Zhu Liyun , Liu Juanbo , Wang Jiangyun , Xie Guoshan
Published: August 2023

Severe erosion phenomena often occur in industrial polycrystalline silicon units, leading to hydrogen leakage accidents and affecting long-term operation. It is favorable to use a computational fluid dynamics (CFD) simulation with the dense discrete phase model (DDPM) and the sub-grid energy-minimization multi-scale (EMMS) drag model to improve the prediction accuracy of complex multiphase erosion phenomena in a connecting pipe of an industrial polycrystalline silicon unit. Furthermore, the effect of droplet the specularity coefficient on boundary conditions is thoroughly considered. The predicted erosion behaviors are consistent with industrial data. The effects of operations parameters were discussed with three-dimensional CFD simulation, including droplet size and hydrogen volume fraction on erosion behaviors. The results indicated that the non-uniform multiphase erosion flow behavior near the wall can be simulated accurately with the EMMS drag model in a coarse mesh. A suitable droplet specularity coefficient such as 0.5 can also improve the accuracy of erosion position. Small liquid droplets, such as those of 30 μm size, will follow the gas phase better and have a lower erosion rate. The inertia effect of large droplets, such as those of 150 μm size, plays a dominant role, resulting in obvious erosion on the elbow walls. The erosion range and thinning rate enlarge with the increase in hydrogen volume fraction. A few silicon solid particles, such as 0.01% volume fraction, change local flow behaviors and probably cause the variation of local erosion positions. The process of erosion deformation first circumferentially extended and then accelerated at the local center position deeper.
Defatting and Defatted Peanuts: A Critical Review on Methods of Oil Extraction and Consideration of Solid Matrix as a By-Product or Intended Target
Authors: Mahfoud Freddy , Assaf Jean , Elias Rudolph , Debs Espérance , Louka Nicolas
Published: August 2023

Peanuts, being crucial crops of global importance, have gained widespread recognition for their versatility and nutritional value. In addition to direct consumption, either with or without treatment, peanuts can be the subject of diverse applications focusing mainly on two distinct objectives: oil extraction and defatting processes. As a result of the first process, a solid matrix is generated as a by-product, necessitating the exploration of strategies for its valorization, while the second process is centered on obtaining protein-rich, low-fat peanuts, for which the oil recovered becomes the by-product. As consumers increasingly seek out plant-based foods for their potential health benefits, this trend is expected to persist, encompassing peanut-based foods as well. This review elucidates the methods used for extracting peanut oil, including mechanical and chemical processes that have been combined with biological or physical pre-treatment techniques. Their primary goals are to maximize oil extraction and unlock the untapped potential of defatted whole peanuts. Additionally, the review addresses the challenges and opportunities in both oil extraction and defatting processes, emphasizing the importance of sustainable practices and efficient resource utilization. The advantages and disadvantages of each method were also evaluated and critically analyzed. Developing novel methods for potential industrial applications and limiting the drawbacks associated with traditional methods became necessary. A comparison in terms of productivity, efficacy, specificity, quality of the extracts, and operating conditions was conducted, which favored the novel methods as being mostly environmentally friendly and cost-efficient.
From “Sangha Forest” (叢林 Conglin) to “Buddhist Academy”: The Influence of Western Knowledge Paradigm on the Chinese Sangha Education in Modern Times
Authors: Liu Yifeng
Published: August 2023

Drawing on Foucault’s theoretical framework of “space and power”, this paper examines the discursive construction of “knowledge” in the context of Chinese Buddhist education. It traces the historical transformation of Chinese Buddhist education from the traditional “Sangha Forest”(the monastic community; 叢林 Conglin) style education to the Buddhist Academy, and analyzes how modern Buddhism reshaped its social image and function from a faith-based to a knowledge-based culture. Furthermore, this paper explores the reasons why modern Buddhism requires “knowledge” as a bridge between its worldly and transcendental dimensions, and the roles of elite laymen and monasteries as “Buddhist Institutes” in the new discursive practice.
Frontal Asymmetry in Pilgrims
Authors: Kéri Szabolcs
Published: August 2023

Individuals with religious or spiritual problems experience depressive and anxiety symptoms, together with changes in cognitive style and coping. These problems are associated with altered frontal asymmetry (left greater than right) during the processing of religious stimuli. The present study aimed to investigate the effect of pilgrimage on frontal asymmetry. The participants were 50 individuals experiencing religious or spiritual problems according to DSM-5 criteria. Some 25 of them participated in a two-week religious pilgrimage, and 25 matched volunteers went on non-religious holidays. We recorded resting-state EEG at baseline and after a religious phase (reading a sacred text and listening to music) (NEUVO–CURRY 8X-system, 256-channel). The frontal asymmetry index was calculated for 1 min epochs by subtracting the left electrode sites’ logarithmically transformed alpha frequency from homologous right leads (F4-F3, F8-F7). Anxiety, depressive symptoms, and rumination were assessed using self-report scales. Psychological and EEG assessments were performed before and after the pilgrimage or holiday. The results revealed that individuals experienced less anxiety, depression, and rumination following the pilgrimage. There was a significant reduction in frontal asymmetry during the processing of religious stimuli in pilgrims. We found no similar changes in volunteers who went on a non-religious holiday. These results indicate that frontal asymmetry and negative emotionality are ameliorated during a pilgrimage in individuals with religious or spiritual problems.
With Whom Should One Worship? A Fresh Perspective on John Calvin’s Liturgical Theology of Physical Proximity and Spiritual Epidemic
Authors: Ha Sam
Published: August 2023

COVID-19 has taught us that whom one surrounds oneself with has a profound influence on one’s well-being. In that light, does whom we worship with matter as well? John Calvin would in fact argue that the people we physically worship with have a great impact on our spiritual life. According to Calvin, if you simply worship with (who he deemed to be) the unrighteous group of people, you will lose your spiritual health or even endanger salvation. This is why he was so insistent on asking the French Protestants to leave France and join him in Geneva. What is striking is that worshipping with the right kind of people does not have that automatic effect. Rather, they have to actively engage in many beneficial activities together, encouraging and empowering one another. This is because, for Calvin, while unrighteousness itself is highly contagious, growing in a nurturing community takes conscious and purposeful effort. In this sense, Calvin explains that idolatry and unrighteousness were a spiritual epidemic that is spread physically, while true piety is acquired through a communal practice of many forms of spiritual exercises. This article will have many important contributions to the field of worship and faith formation. Most notably, while scholars have long been addressing Calvin’s view of active practices during worship which help faith formation, I will show that that is not all there is. Instead, I will demonstrate how even simple physical proximity in worship can have an impact on one’s spiritual growth in Calvin’s thought. Another important contribution of this article would be offering a clearer presentation of Calvin’s sacramental theology of body and soul. Scholars have long been arguing that, for Calvin, the bodily participation in a Roman Catholic mass while believing in (what was for him) the true gospel was a serious sin of idolatry and hypocrisy. My article will further develop this idea by noting that, according to Calvin, not only is it wrong to do one thing with one’s body and another with one’s soul but having one’s body in a negative environment is harmful to one’s soul. If one’s body is surrounded by other people who do not believe in the true gospel, it would have a devastating impact on one’s soul. In other words, for Calvin, the body and soul influence each other in a way that has sacramental and developmental implications.
Mediated Morality as a Middle Position in Understanding the Relation between God and Morality
Authors: Areklett Amund Tobias Måge , Søvik Atle Ottesen
Published: August 2023

How should we understand the relation between God and morality? This article aims to address this question by constructing a theistic metaethical theory informed by postphenomenological mediation theory. According to postphenomenological mediation theory, properties and values are not independent entities but are instead mutually constituted through the relationships that they participate in. By emphasizing relationships and understanding goodness as harmony, the theory allows God and creation to jointly constitute goodness. This alternative theory is compared to the metaethical theories proposed by Robert M. Adams and Mark C. Murphy, which represent the two primary strands of theistic metaethics: theological voluntarism and natural law theory, respectively. The alternative theory exhibits certain advantages and resolves some of the issues found in Adams’ and Murphy’s theories.
Adversarial Deep Transfer Learning in Fault Diagnosis: Progress, Challenges, and Future Prospects
Authors: Guo Yu , Zhang Jundong , Sun Bin , Wang Yongkang
Published: August 2023

Deep Transfer Learning (DTL) signifies a novel paradigm in machine learning, merging the superiorities of deep learning in feature representation with the merits of transfer learning in knowledge transference. This synergistic integration propels DTL to the forefront of research and development within the Intelligent Fault Diagnosis (IFD) sphere. While the early DTL paradigms, reliant on fine-tuning, demonstrated effectiveness, they encountered considerable obstacles in complex domains. In response to these challenges, Adversarial Deep Transfer Learning (ADTL) emerged. This review first categorizes ADTL into non-generative and generative models. The former expands upon traditional DTL, focusing on the efficient transference of features and mapping relationships, while the latter employs technologies such as Generative Adversarial Networks (GANs) to facilitate feature transformation. A thorough examination of the recent advancements of ADTL in the IFD field follows. The review concludes by summarizing the current challenges and future directions for DTL in fault diagnosis, including issues such as data imbalance, negative transfer, and adversarial training stability. Through this cohesive analysis, this review aims to offer valuable insights and guidance for the optimization and implementation of ADTL in real-world industrial scenarios.
An Improved BM3D Algorithm Based on Image Depth Feature Map and Structural Similarity Block-Matching
Authors: Cao Jia , Qiang Zhenping , Lin Hong , He Libo , Dai Fei
Published: August 2023

We propose an improved BM3D algorithm for block-matching based on UNet denoising network feature maps and structural similarity (SSIM). In response to the traditional BM3D algorithm that directly performs block-matching on a noisy image, without considering the deep-level features of the image, we propose a method that performs block-matching on the feature maps of the noisy image. In this method, we perform block-matching on multiple depth feature maps of a noisy image, and then determine the positions of the corresponding similar blocks in the noisy image based on the block-matching results, to obtain the set of similar blocks that take into account the deep-level features of the noisy image. In addition, we improve the similarity measure criterion for block-matching based on the Structural Similarity Index, which takes into account the pixel-by-pixel value differences in the image blocks while fully considering the structure, brightness, and contrast information of the image blocks. To verify the effectiveness of the proposed method, we conduct extensive comparative experiments. The experimental results demonstrate that the proposed method not only effectively enhances the denoising performance of the image, but also preserves the detailed features of the image and improves the visual quality of the denoised image.
A Pressure-Based Multiphase Flowmeter: Proof of Concept
Authors: Ramakrishnan Vijay , Arsalan Muhammad
Published: August 2023

Multiphase flowmeters (MPFMs) measure the flow rates of oil, gas, and brine in a pipeline. MPFMs provide remote access to real-time well production data that are essential for efficient oil field operations. Most MPFMs are complex systems requiring frequent maintenance. An MPFM that is operationally simple and accurate is highly sought after in the energy industry. This paper describes an MPFM that uses only pressure sensors to measure gas and liquid flow rates. The design is an integration of a previously developed densitometer with an innovative Venturi-type flowmeter. New computing models with strong analytical foundations were developed, aided by empirical correlations and machine-learning-based flow-regime identification. A prototype was experimentally validated in a multiphase flow loop over a wide range of field-like conditions. The accuracy of the MPFM was compared to that of other multiphase metering techniques from similar studies. The results point to a robust, practical MPFM.
A Systematic Literature Review on Cyber Threat Intelligence for Organizational Cybersecurity Resilience
Authors: Saeed Saqib , Suayyid Sarah A. , Al-Ghamdi Manal S. , Al-Muhaisen Hayfa , Almuhaideb Abdullah M.
Published: August 2023

Cybersecurity is a significant concern for businesses worldwide, as cybercriminals target business data and system resources. Cyber threat intelligence (CTI) enhances organizational cybersecurity resilience by obtaining, processing, evaluating, and disseminating information about potential risks and opportunities inside the cyber domain. This research investigates how companies can employ CTI to improve their precautionary measures against security breaches. The study follows a systematic review methodology, including selecting primary studies based on specific criteria and quality valuation of the selected papers. As a result, a comprehensive framework is proposed for implementing CTI in organizations. The proposed framework is comprised of a knowledge base, detection models, and visualization dashboards. The detection model layer consists of behavior-based, signature-based, and anomaly-based detection. In contrast, the knowledge base layer contains information resources on possible threats, vulnerabilities, and dangers to key assets. The visualization dashboard layer provides an overview of key metrics related to cyber threats, such as an organizational risk meter, the number of attacks detected, types of attacks, and their severity level. This relevant systematic study also provides insight for future studies, such as how organizations can tailor their approach to their needs and resources to facilitate more effective collaboration between stakeholders while navigating legal/regulatory constraints related to information sharing.
Wireless Sensor Network-Based Rockfall and Landslide Monitoring Systems: A Review
Authors: Ragnoli Mattia , Scarsella Massimo , Leoni Alfiero , Ferri Giuseppe , Stornelli Vincenzo
Published: August 2023

Rockfalls and landslide events are caused by different factors among which are included geomorphological and climatic factors and also human interaction. Therefore, the economic and social impacts can be significant and the remote monitoring of such hazards has become an essential topic in various applications. Wireless sensor networks (WSNs) are well suited for the deployment of monitoring systems, benefiting from the different technologies and topologies that are available and evolving nowadays. This review paper aims to summarize and overview the up-to-date state of the art of rockfall and landslide monitoring systems based on WSNs. The implementation and methods were analyzed for each solution, along with the system architecture and relevant hardware aspects. All the retrieved data were used to analyze the current trends and future possibilities in the field of WSN geohazard monitoring.
Automatic Modulation Classification Based on CNN-Transformer Graph Neural Network
Authors: Wang Dong , Lin Meiyan , Zhang Xiaoxu , Huang Yonghui , Zhu Yan
Published: August 2023

In recent years, neural network algorithms have demonstrated tremendous potential for modulation classification. Deep learning methods typically take raw signals or convert signals into time–frequency images as inputs to convolutional neural networks (CNNs) or recurrent neural networks (RNNs). However, with the advancement of graph neural networks (GNNs), a new approach has been introduced involving transforming time series data into graph structures. In this study, we propose a CNN-transformer graph neural network (CTGNet) for modulation classification, to uncover complex representations in signal data. First, we apply sliding window processing to the original signals, obtaining signal subsequences and reorganizing them into a signal subsequence matrix. Subsequently, we employ CTGNet, which adaptively maps the preprocessed signal matrices into graph structures, and utilize a graph neural network based on GraphSAGE and DMoNPool for classification. Extensive experiments demonstrated that our method outperformed advanced deep learning techniques, achieving the highest recognition accuracy. This underscores CTGNet’s significant advantage in capturing key features in signal data and providing an effective solution for modulation classification tasks.
Time-Distributed Framework for 3D Reconstruction Integrating Fringe Projection with Deep Learning
Authors: Nguyen Andrew-Hieu , Wang Zhaoyang
Published: August 2023

In recent years, integrating structured light with deep learning has gained considerable attention in three-dimensional (3D) shape reconstruction due to its high precision and suitability for dynamic applications. While previous techniques primarily focus on processing in the spatial domain, this paper proposes a novel time-distributed approach for temporal structured-light 3D shape reconstruction using deep learning. The proposed approach utilizes an autoencoder network and time-distributed wrapper to convert multiple temporal fringe patterns into their corresponding numerators and denominators of the arctangent functions. Fringe projection profilometry (FPP), a well-known temporal structured-light technique, is employed to prepare high-quality ground truth and depict the 3D reconstruction process. Our experimental findings show that the time-distributed 3D reconstruction technique achieves comparable outcomes with the dual-frequency dataset (p = 0.014) and higher accuracy than the triple-frequency dataset (p = 1.029 × 10−9), according to non-parametric statistical tests. Moreover, the proposed approach’s straightforward implementation of a single training network for multiple converters makes it more practical for scientific research and industrial applications.
Touchless Heart Rate Monitoring from an Unmanned Aerial Vehicle Using Videoplethysmography
Authors: Pająk Anna , Przybyło Jaromir , Augustyniak Piotr
Published: August 2023

Motivation: The advancement of preventive medicine and, subsequently, telemedicine drives the need for noninvasive and remote measurements in patients’ natural environments. Heart rate (HR) measurements are particularly promising and extensively researched due to their quick assessment and comprehensive representation of patients’ conditions. However, in scenarios such as endurance training or emergencies, where HR measurement was not anticipated and direct access to victims is limited, no method enables obtaining HR results that are suitable even for triage. Methods: This paper presents the possibility of remotely measuring of human HR from a series of in-flight videos using videoplethysmography (VPG) along with skin detection, human pose estimation and image stabilization methods. An unmanned aerial vehicle (UAV) equipped with a camera captured ten segments of video footage featuring volunteers engaged in free walking and running activities in natural sunlight. The human pose was determined using the OpenPose algorithm, and subsequently, skin areas on the face and forearms were identified and tracked in consecutive frames. Ultimately, HR was estimated using several VPG methods: the green channel (G), green-red difference (GR), excess green (ExG), independent component analysis (ICA), and a plane orthogonal to the skin (POS). Results: When compared to simultaneous readings from a reference ECG-based wearable recorder, the root-mean-squared error ranged from 17.7 (G) to 27.7 (POS), with errors of less than 3.5 bpm achieved for the G and GR methods. Conclusions: These results demonstrate the acceptable accuracy of touchless human pulse measurement with the accompanying UAV-mounted camera. The method bridges the gap between HR-transmitting wearables and emergency HR recorders, and it has the potential to be advantageous in training or rescue scenarios in mountain, water, disaster, or battlefield settings.
Use of Alcaligenes faecalis to Reduce Coliforms and Enhance the Stabilization of Faecal Sludge
Authors: Loiko Nataliya , Kanunnikov Oleg , Litti Yuriy
Published: August 2023

The disposal of human faecal sludge (FS) is one of the biggest environmental problems. It can be solved by using FS as an agricultural fertilizer. However, this is hampered by the presence of pathogenic microflora and high organic matter content in FS. This paper proposes a novel treatment approach for FS to address these issues. It consists of the preliminary aerobic incubation of FS with the bioaugmentation of bacterial culture Alcaligenes faecalis DOS7. A. faecalis has been shown to inhibit the growth of various microorganisms, including coliforms (Escherichia coli). For the treatment of FS, three tanks with a volume of 1 m3 each, equipped with a mixing and aeration system, were used. A. faecalis culture was introduced into two experimental tanks at a concentration of 106 and 6.5 × 106 cells/mL. The 11-day incubation in the experimental tanks resulted in the decomposition of organic matter in the FS that was several times faster than in the control (p < 0.05). Total suspended solids decreased 2.5–5-fold, chemical oxygen demand decreased 1.8-fold, 5-day biochemical oxygen demand decreased 1.5–2-fold. At the same time, after 4 days of incubation, no coliforms were detected in the experimental tanks, and in the control, coliforms accounted for 13.9% of the total number of cells after 11 days of incubation. The proposed method of FS pretreatment is a real alternative to the existing ones and can be used both individually and in combination with other methods, for example, composting.
Increased Riparian Vegetation Density and Its Effect on Flow Conditions
Authors: Kiss Tímea , Fehérváry István
Published: August 2023

The physical and biological structure of riparian vegetation fundamentally influences floodplain roughness, and thus the flood velocity and flood levels of a river. The study aims to provide detailed spatial data on the vegetation density of a floodplain, and to model the effect of the actual vegetation and various scenarios on flow conditions. LiDAR data were applied to evaluate the density and roughness of the submerged understory vegetation over the densely vegetated floodplain of Lower Tisza, Hungary. Then, HEC–RAS 2D modelling was applied to analyse the effect of the actual vegetation on flow conditions. Further scenarios were also created to predict the effect of (i) invasive plant control, (ii) no maintenance, and (iii) riparian vegetation restoration (meadows). According to the results, since the 19th Century, the increased vegetation density is responsible for a 17-cm flood level increase, and if the vegetation grows even denser, a further 7 cm could be expected. As the vegetation density increases, the overbank flow velocity decreases, and the crevasses and flood conveyance zones gradually lose their function. Simultaneously, the flow velocity increases in the channel (from 1 m/s to 1.4 m/s), resulting in an incision. Applying LiDAR-based 2D flow modelling makes it possible to plan sustainable riparian vegetation maintenance (e.g., forestry, invasive species clearance) from both ecology and flood control perspectives.
How Can Stories in Primary Education Support Sustainable Development in Bangladesh?
Authors: Tasnim Saria , Hossain Amzad , Marinova Dora
Published: August 2023

Stories are considered to be the most popular form of lore, which can facilitate the moral and ethical deliberation of sustainability for our children. It is evident that children respond better to stories than any other form of communication. Once the stories end, the lessons remain. The values tangled with the lesson transmit as they grow. Stories have always been instrumental and the most conventional way of teaching values by using illustrations from our lives. The major aim of this paper is to explore the values expressed in Bengali childlore through stories and tales and develop a framework by using a scaffolding and mapping approach. This framework attempts to analyse two commonly recognised stories, namely “Shukhu and Dukhu” and “Jackal, The Judge”, by scaffolding them with the generally acknowledged principles of sustainability and mapping them to investigate how stories can influence children to build a pro-sustainability attitude. This approach has been chosen, as recent research already points out the issues in implementing sustainability in education, but no one has yet found the way forward. The premise at the core of this theoretical article is that an interdisciplinary approach and different pedagogical tools could help build the bridge towards implementing sustainability in education as well as in society.