bluuebunny/crossref_metadata_2025 huggingface dataset:
Nonreligious Afterlife: Emerging Understandings of Death and Dying
Authors: Miller Chris , Beaman Lori G.
Published: January 2024

Death Cafés are informal events that bring people together for conversations about death and related issues. These events connect strangers from across a range of backgrounds, including healthcare workers, hospice volunteers, and funeral directors, among others. Based on an analysis of focus groups and interviews with Death Café attendees, this paper explores how participants construct and express conceptions of the process of dying and what happens after we die. Ideas about the afterlife have historically been shaped by a religious outlooks and identities. However, nonreligious lifestances have shifted how people understand death and dying. We suggest that notions of continuity of life are not the purview of religious people. Rather, participants in Death Cafés draw simultaneously on many ideas, and reveal ways of conceptualizing life after death—in various forms—without the guidance of religion. Based on conversations with attendees about their outlooks on death (and what may happen after death), our data reveals four main typologies of afterlife imaginaries, which we label cessation, unknown, energy, and transition. Among the diverse perspectives shared, we argue for the emergence of an immanent afterlife outlook.
Ecumenical Footprints in Nigeria: Pathways and Detours in Search of Christian Unity
Authors: Konye Michael
Published: January 2024

The unity of the Persons of the Trinity is the source and highest exemplar of Christian unity which all ecumenical initiatives seek. During his earthly ministry, our Lord Jesus Christ prayed for the unity of Christians (John 17:21). This prayer of Jesus furnishes us with the fundamental inspiration for the ecumenical movement in all its dimensions of expression. Right from the beginning, the Christian church has experienced rifts in both the West and the East. The modern ecumenical movement is an attempt to restore Christian unity against the background of 16th century divisions attendant upon the Protestant Reformation. It is also conducted in hindsight of the Protestant Reformation that the 19th and 20th century missionary activities of Christian churches from Europe in Nigeria took place. Several historical factors have shaped the successes and failures of significant missionary endeavors. This article highlights a few of those historical factors in a bid to identify the roots of discord and footprints of ecumenism at the beginning of the establishment of Christian churches in Nigeria. The goal intended to be realized through this historical excursus is to engender a livelier ecumenical hope for Christian unity in Nigeria while maintaining the already-achieved progress made so far, as well as countering further divisions.
PriTKT: A Blockchain-Enhanced Privacy-Preserving Electronic Ticket System for IoT Devices
Authors: Zhan Yonghua , Yuan Feng , Shi Rui , Shi Guozhen , Dong Chen
Published: January 2024

Electronic tickets (e-tickets) are gradually being adopted as a substitute for paper-based tickets to bring convenience to customers, corporations, and governments. However, their adoption faces a number of practical challenges, such as flexibility, privacy, secure storage, and inability to deploy on IoT devices such as smartphones. These concerns motivate the current research on e-ticket systems, which seeks to ensure the unforgeability and authenticity of e-tickets while simultaneously protecting user privacy. Many existing schemes cannot fully satisfy all these requirements. To improve on the current state-of-the-art solutions, this paper constructs a blockchain-enhanced privacy-preserving e-ticket system for IoT devices, dubbed PriTKT, which is based on blockchain, structure-preserving signatures (SPS), unlinkable redactable signatures (URS), and zero-knowledge proofs (ZKP). It supports flexible policy-based ticket purchasing and ensures user unlinkability. According to the data minimization and revealing principle of GDPR, PriTKT empowers users to selectively disclose subsets of (necessary) attributes to sellers as long as the disclosed attributes satisfy ticket purchasing policies. In addition, benefiting from the decentralization and immutability of blockchain, effective detection and efficient tracing of double spending of e-tickets are supported in PriTKT. Considering the impracticality of existing e-tickets schemes with burdensome ZKPs, we replace them with URS/SPS or efficient ZKP to significantly improve the efficiency of ticket issuing and make it suitable for use on smartphones.
Pb2+ Ion Sensors Employing Gold Etching Process: Comparative Investigation on Au Nanorods and Au Nanotriangles
Authors: Park Eun Jin , Ha Tai Hwan
Published: January 2024

The leaching phenomenon of gold (Au) nanomaterials by Pb2+ ions in the presence of 2-mercaptoethanol (2-ME) and thiosulfate (S2O32− ion) has been systematically applied to a Pb2+ ion sensor. To further investigate the role of Pb2+ ions in sensors containing Au nanomaterials, we revisited the leaching conditions for Au nanorods and compared them with the results for Au nanotriangles. By monitoring the etching rate, it was revealed that Pb2+ ions were important for the acceleration of the etching rate mainly driven by 2-ME and S2O32− pairs, and nanomolar detection of Pb2+ ions were shown to be promoted through this catalytic effect. Using the etchant, the overall size of the Au nanorods decreased but showed an unusual red-shift in UV-Vis spectrum indicating increase of aspect ratio. Indeed, the length of Au nanorods decreased by 9.4% with the width decreasing by 17.4% over a 30-min reaction time. On the other hand, the Au nanotriangles with both flat sides surrounded mostly by dense Au{111} planes showed ordinary blue-shift in UV-Vis spectrum as the length of one side was reduced by 21.3%. By observing the changes in the two types of Au nanomaterials, we inferred that there was facet-dependent alloy formation with lead, and this difference resulted in Au nanotriangles showing good sensitivity, but lower detection limits compared to the Au nanorods.
Non-Invasive Estimation of Intracranial Pressure-Derived Cerebrovascular Reactivity Using Near-Infrared Spectroscopy Sensor Technology in Acute Neural Injury: A Time-Series Analysis
Authors: Gomez Alwyn , Froese Logan , Bergmann Tobias J. G. , Sainbhi Amanjyot Singh , Vakitbilir Nuray , Islam Abrar , Stein Kevin Y. , Marquez Izabella , Ibrahim Younis , Zeiler Frederick A.
Published: January 2024

The contemporary monitoring of cerebrovascular reactivity (CVR) relies on invasive intracranial pressure (ICP) monitoring which limits its application. Interest is shifting towards near-infrared spectroscopic regional cerebral oxygen saturation (rSO2)-based indices of CVR which are less invasive and have improved spatial resolution. This study aims to examine and model the relationship between ICP and rSO2-based indices of CVR. Through a retrospective cohort study of prospectively collected physiologic data in moderate to severe traumatic brain injury (TBI) patients, linear mixed effects modeling techniques, augmented with time-series analysis, were utilized to evaluate the ability of rSO2-based indices of CVR to model ICP-based indices. It was found that rSO2-based indices of CVR had a statistically significant linear relationship with ICP-based indices, even when the hierarchical and autocorrelative nature of the data was accounted for. This strengthens the body of literature indicating the validity of rSO2-based indices of CVR and potential greatly expands the scope of CVR monitoring.
Predicting Receiver Characteristics without Sensors in an LC–LC Tuned Wireless Power Transfer System Using Machine Learning
Authors: Kim Minhyuk , Niada Wend Yam Ella Flore , Park Sangwook
Published: January 2024

Improvement of wireless power transfer (WPT) systems is necessary to tackle issues of power transfer efficiency, high costs due to sensor and communication requirements between the transmitter (Tx) and receiver (Rx), and maintenance problems. Analytical techniques and hardware-based synchronization research for Rx-sensorless WPT may not always have been available or accurate. To address these limitations, researchers have recently employed machine learning (ML) to improve efficiency and accuracy. The objective of this work was to replace Tx–Rx communication with ML, utilizing Tx-side parameters to predict the load and coupling coefficients on an LC–LC tuned WPT system. Based on current and voltage features collected on the Tx-side for various load and coupling coefficient values, we developed two models for each load and coupling prediction. This study demonstrated that the extra trees regressor effectively predicted the characteristics of LC–LC tuned WPT systems, with coefficients of determination of 0.967 and 0.996 for load and coupling, respectively. Additionally, the mean absolute percentage errors were 0.11% and 0.017%.
Research on Oracle Technology Based on Multi-Threshold Aggregate Signature Algorithm and Enhanced Trustworthy Oracle Reputation Mechanism
Authors: Wang Zhiyuan , Gao Mingan , Lu Gehao
Published: January 2024

In the realm of IoT sensor data security, particularly in areas like agricultural product traceability, the challenges of ensuring product origin and quality are paramount. This research presents a novel blockchain oracle solution integrating an enhanced MTAS signature algorithm derived from the Schnorr signature algorithm. The key improvement lies in the automatic adaptation of flexible threshold values based on the current scenario, catering to diverse security and efficiency requirements. Utilizing the continuously increasing block height of the blockchain as a pivotal blinding parameter, our approach strengthens signature verifiability and security. By combining the block height with signature parameters, we devise a distinctive signing scheme reliant on a globally immutable timestamp. Additionally, this study introduces a reliable oracle reputation mechanism for monitoring and assessing oracle node performance, maintaining both local and global reputations. This mechanism leverages smart contracts to evaluate each oracle’s historical service, penalizing or removing nodes engaged in inappropriate behaviors. Experimental results highlight the innovative contributions of our approach to enhancing on-chain efficiency and fortifying security during the on-chain process, offering promising advancements for secure and efficient IoT sensor data transmission.
Evaluation of Inference Performance of Deep Learning Models for Real-Time Weed Detection in an Embedded Computer
Authors: Mwitta Canicius , Rains Glen C. , Prostko Eric
Published: January 2024

The knowledge that precision weed control in agricultural fields can reduce waste and increase productivity has led to research into autonomous machines capable of detecting and removing weeds in real time. One of the driving factors for weed detection is to develop alternatives to herbicides, which are becoming less effective as weed species develop resistance. Advances in deep learning technology have significantly improved the robustness of weed detection tasks. However, deep learning algorithms often require extensive computational resources, typically found in powerful computers that are not suitable for deployment in robotic platforms. Most ground rovers and UAVs utilize embedded computers that are portable but limited in performance. This necessitates research into deep learning models that are computationally lightweight enough to function in embedded computers for real-time applications while still maintaining a base level of detection accuracy. This paper evaluates the weed detection performance of three real-time-capable deep learning models, YOLOv4, EfficientDet, and CenterNet, when run on a deep-learning-enabled embedded computer, an Nvidia Jetson Xavier AGX. We tested the accuracy of the models in detecting 13 different species of weeds and assesses their real-time viability through their inference speeds on an embedded computer compared to a powerful deep learning PC. The results showed that YOLOv4 performed better than the other models, achieving an average inference speed of 80 ms per image and 14 frames per second on a video when run on an imbedded computer, while maintaining a mean average precision of 93.4% at a 50% IoU threshold. Furthermore, recognizing that some real-world applications may require even greater speed, and that the detection program would not be the only task running on the embedded computer, a lightweight version of the YOLOv4 model, YOLOv4-tiny, was tested for improved performance in an embedded computer. YOLOv4-tiny impressively achieved an average inference speed of 24.5 ms per image and 52 frames per second, albeit with a slightly reduced mean average precision of 89% at a 50% IoU threshold, making it an ideal choice for real-time weed detection.
Enhancing Aircraft Safety through Advanced Engine Health Monitoring with Long Short-Term Memory
Authors: Yildirim Suleyman , Rana Zeeshan A.
Published: January 2024

Predictive maintenance holds a crucial role in various industries such as the automotive, aviation and factory automation industries when it comes to expensive engine upkeep. Predicting engine maintenance intervals is vital for devising effective business management strategies, enhancing occupational safety and optimising efficiency. To achieve predictive maintenance, engine sensor data are harnessed to assess the wear and tear of engines. In this research, a Long Short-Term Memory (LSTM) architecture was employed to forecast the remaining lifespan of aircraft engines. The LSTM model was evaluated using the NASA Turbofan Engine Corruption Simulation dataset and its performance was benchmarked against alternative methodologies. The results of these applications demonstrated exceptional outcomes, with the LSTM model achieving the highest classification accuracy at 98.916% and the lowest mean average absolute error at 1.284%.
An Electrical Resistance Diagnostic for Conductivity Monitoring in Laser Powder Bed Fusion
Authors: Mukherjee Saptarshi , Benavidez Edward , Crumb Michael , Calta Nicholas P.
Published: January 2024

With the growing interest in metal additive manufacturing using laser powder bed fusion (LPBF), there is a need for advanced in-situ nondestructive evaluation (NDE) methods that can dynamically monitor manufacturing process-related variations, that can be used as a feedback mechanism to further improve the manufacturing process, leading to parts with improved microstructural properties and mechanical properties. Current NDE techniques either lack sensitivity beyond build layer, are costly or time-consuming, or are not compatible for in-situ integration. In this research, we develop an electrical resistance diagnostic for in-situ monitoring of powder fused regions during laser powder bed fusion printing. The technique relies on injecting current into the build plate and detecting voltage differences from conductive variations during printing using a simple, cheap four-point electrode array directly connected to the build plate. A computational model will be utilized to determine sensitivities of the approach, and preliminary experiments will be performed during the printing process to test the overall approach.
The Use of Electrocardiogram Smartwatches in Patients with Cardiac Implantable Electrical Devices
Authors: Strik Marc , Ploux Sylvain , Zande Joske van der , Velraeds Anouk , Fontagne Leslie , Haïssaguerre Michel , Bordachar Pierre
Published: January 2024

Unlimited access to ECGs using an over-the-counter smartwatch constitutes a real revolution for our discipline, and the application is rapidly expanding to include patients with cardiac implantable electronic devices (CIEDs) such as pacemakers (PMs) and implantable cardioverter defibrillators (ICDs). CIEDs require periodic evaluation and adjustment by healthcare professionals. In addition, implanted patients often present with symptoms that may be related to their PMs or ICDs. An ECG smartwatch could reveal information about device functioning, confirm normal device function, or aid in the case of device troubleshooting. In this review, we delve into the available evidence surrounding smartwatches with ECG registration and their integration into the care of patients with implanted pacemakers and ICDs. We explore safety considerations and the benefits and limitations associated with these wearables, drawing on relevant studies and case series from our own experience. By analyzing the current landscape of this emerging technology, we aim to provide a comprehensive overview that facilitates informed decision-making for both healthcare professionals and patients.
RC-SLAM: Road Constrained Stereo Visual SLAM System Based on Graph Optimization
Authors: Zhu Yuan , An Hao , Wang Huaide , Xu Ruidong , Wu Mingzhi , Lu Ke
Published: January 2024

Intelligent vehicles are constrained by road, resulting in a disparity between the assumed six degrees of freedom (DoF) motion within the Visual Simultaneous Localization and Mapping (SLAM) system and the approximate planar motion of vehicles in local areas, inevitably causing additional pose estimation errors. To address this problem, a stereo Visual SLAM system with road constraints based on graph optimization is proposed, called RC-SLAM. Addressing the challenge of representing roads parametrically, a novel method is proposed to approximate local roads as discrete planes and extract parameters of local road planes (LRPs) using homography. Unlike conventional methods, constraints between the vehicle and LRPs are established, effectively mitigating errors arising from assumed six DoF motion in the system. Furthermore, to avoid the impact of depth uncertainty in road features, epipolar constraints are employed to estimate rotation by minimizing the distance between road feature points and epipolar lines, robust rotation estimation is achieved despite depth uncertainties. Notably, a distinctive nonlinear optimization model based on graph optimization is presented, jointly optimizing the poses of vehicle trajectories, LPRs, and map points. The experiments on two datasets demonstrate that the proposed system achieved more accurate estimations of vehicle trajectories by introducing constraints between the vehicle and LRPs. The experiments on a real-world dataset further validate the effectiveness of the proposed system.
MagnetoShield: A Novel Open-Source Magnetic Levitation Benchmark Device for Mechatronics Education and Research
Authors: Takács Gergely , Mihalík Jakub , Gulan Martin , Vargová Anna , Mikuláš Erik , Ožana Štepán
Published: January 2024

This article presents an open-source device illustrating the well-known magnetic levitation experiment. The uniqueness of this particular device lies in its exceptionally small dimensions, affordability and availability, which makes it a perfect design for take-home experiments for education but it can also serve as a referential design for testing various control algorithms in research. In addition, this paper provides a comprehensive hardware design for reproducibility along with the detailed derivation of the mathematical model, system identification and validation. Moreover, the introduced hardware comes with an easy-to-use open-source application programming interface in C/C++ for the Arduino IDE, Simulink and CircuitPython. REXYGEN, another environment similar to Simulink, had also been used to demonstrate the capabilities of the MagnetoShield.
Reliability and Validity of Shore Hardness in Plantar Soft Tissue Biomechanics
Authors: Tonna Redent , Chatzistergos Panagiotis E. , Wyatt Otis , Chockalingam Nachiappan
Published: January 2024

Shore hardness (SH) is a cost-effective and easy-to-use method to assess soft tissue biomechanics. Its use for the plantar soft tissue could enhance the clinical management of conditions such as diabetic foot complications, but its validity and reliability remain unclear. Twenty healthy adults were recruited for this study. Validity and reliability were assessed across six different plantar sites. The validity was assessed against shear wave (SW) elastography (the gold standard). SH was measured by two examiners to assess inter-rater reliability. Testing was repeated following a test/retest study design to assess intra-rater reliability. SH was significantly correlated with SW speed measured in the skin or in the microchamber layer of the first metatarsal head (MetHead), third MetHead and rearfoot. Intraclass correlation coefficients and Bland–Altman plots of limits of agreement indicated satisfactory levels of reliability for these sites. No significant correlation between SH and SW elastography was found for the hallux, 5th MetHead or midfoot. Reliability for these sites was also compromised. SH is a valid and reliable measurement for plantar soft tissue biomechanics in the first MetHead, the third MetHead and the rearfoot. Our results do not support the use of SH for the hallux, 5th MetHead or midfoot.
A Fusion Algorithm Based on a Constant Velocity Model for Improving the Measurement of Saccade Parameters with Electrooculography
Authors: Gunawardane Palpolage Don Shehan Hiroshan , MacNeil Raymond Robert , Zhao Leo , Enns James Theodore , de Silva Clarence Wilfred , Chiao Mu
Published: January 2024

Electrooculography (EOG) serves as a widely employed technique for tracking saccadic eye movements in a diverse array of applications. These encompass the identification of various medical conditions and the development of interfaces facilitating human–computer interaction. Nonetheless, EOG signals are often met with skepticism due to the presence of multiple sources of noise interference. These sources include electroencephalography, electromyography linked to facial and extraocular muscle activity, electrical noise, signal artifacts, skin-electrode drifts, impedance fluctuations over time, and a host of associated challenges. Traditional methods of addressing these issues, such as bandpass filtering, have been frequently utilized to overcome these challenges but have the associated drawback of altering the inherent characteristics of EOG signals, encompassing their shape, magnitude, peak velocity, and duration, all of which are pivotal parameters in research studies. In prior work, several model-based adaptive denoising strategies have been introduced, incorporating mechanical and electrical model-based state estimators. However, these approaches are really complex and rely on brain and neural control models that have difficulty processing EOG signals in real time. In this present investigation, we introduce a real-time denoising method grounded in a constant velocity model, adopting a physics-based model-oriented approach. This approach is underpinned by the assumption that there exists a consistent rate of change in the cornea-retinal potential during saccadic movements. Empirical findings reveal that this approach remarkably preserves EOG saccade signals, resulting in a substantial enhancement of up to 29% in signal preservation during the denoising process when compared to alternative techniques, such as bandpass filters, constant acceleration models, and model-based fusion methods.
Design of a Shape-Memory-Alloy-Based Carangiform Robotic Fishtail with Improved Forward Thrust
Authors: Koiri Mithilesh Kumar , Dubey Vineet , Sharma Anuj Kumar , Chuchala Daniel
Published: January 2024

Shape memory alloys (SMAs) have become the most common choice for the development of mini- and micro-type soft bio-inspired robots due to their high power-to-weight ratio, ability to be installed and operated in limited space, silent and vibration-free operation, biocompatibility, and corrosion resistance properties. Moreover, SMA spring-type actuators are used for developing different continuum robots, exhibiting high degrees of freedom and flexibility. Spring- or any elastic-material-based antagonistic or biasing force is mostly preferred among all other biasing techniques to generate periodic oscillation of SMA actuator-based robotic body parts. In this model-based study, SMA-based spring-type actuators were used to develop a carangiform-type robotic fishtail. Fin size optimization for the maximization of forward thrust was performed for the developed system by varying different parameters, such as caudal fin size, current through actuators, pulse-width modulation signal (PWM), and operating depth. A caudal fin with a mixed fin pattern between the Lunate and Fork “Lunafork” and a fin area of approximately 5000 mm2 was found to be the most effective for the developed system. The maximum forward thrust developed by this fin was recorded as 40 gmf at an operation depth of 12.5 cm in a body of still water.
Postoperative Cast Immobilization Might Be Unnecessary after Pelvic Osteotomy for Children with Developmental Hip Dysplasia: A Systematic Review
Authors: Mai Mohamed , van Stralen Renée A. , Moerman Sophie , van Bergen Christiaan J. A.
Published: January 2024

Background: Developmental dysplasia of the hip (DDH) is a common disorder of atypical hip development. Pelvic osteotomy (e.g., according to Salter, Pemberton or Dega) may be indicated for children with DDH at walking age. The most popular postoperative treatment is a hip spica cast. Alternative postoperative options include abduction braces and non-weightbearing protocols combined with physical therapy. The aim of this systematic review was to determine the most effective form of postoperative treatment after unilateral pelvic osteotomy in children with DDH in terms of clinical and radiological outcomes and complications. Methods: A systematic review was conducted and reported according to Preferred Reporting Items for Systematic Reviews and Meta-Analysis 2020 guidelines and registered in the international prospective register of systematic reviews. Articles were selected from PubMed, Embase and Cochrane databases. The quality of all (non-)randomized included studies was assessed using the Methodological Index for Non-Randomized Studies (MINORS) criteria. Results: The search strategy yielded 3524 articles. Fourteen articles with 367 total hips were included in this review. A total of 312 hips were treated with spica casts, 49 with abduction braces and 6 with non-weightbearing protocols. The quality of evidence was moderate (MINORS, 3–12 points). All types of postoperative treatments had good clinical outcomes overall, without secondary displacement of the osteotomy. Clinical outcomes for spica casts were reported according to McKay’s criteria in 135 hips, with 123 excellent and 12 good results. Clinical outcomes for abduction braces showed satisfaction for all parents (49 of 49). The radiological outcome was overall well preserved with any postoperative treatment. There was a higher complication rate with the use of hip spica casts, including avascular necrosis, pain complaints and superficial infections. Conclusion: This systematic review showed no benefit of postoperative spica casts compared with abduction braces and avoidance of weightbearing after simple pelvic osteotomy for residual DDH.
The Impact of Green Space on University Students’ Mental Health: The Mediating Roles of Solitude Competence and Perceptual Restoration
Authors: Zhang Jun , Jin Jinghua , Liang Yimeng
Published: January 2024

With the prevalence of mental health problems among college students, perceptual recovery and the sensory dimensions of perception (PSD) have emerged as crucial environment-related factors for psychological well-being. However, there has been relatively limited research on how these factors directly and indirectly impact the restoration experience of college students in green spaces on campuses. Therefore, the aim of this study was to determine the influence of college students’ intrinsic motivation on their psychological well-being when exposed to campus green spaces. Special attention was given to the role of solitude and perceptual recovery in this process. Research Methodology: Based on a literature review and field research, we classified campus green spaces into eight types based on perceptual dimensions. We collected 550 questionnaires on campus, and the data processing involved structural equation modeling (SEM) and mediation analysis. Findings: A positive correlation was found between perceived sensory dimensions and the recovery experience. College students’ perceptual recovery and ability to be alone emerged as mediating variables in this process. In essence, this study sheds light on the mechanism through which intrinsic motivation impacts the mental health of college students when they engage with campus green spaces.
Unconventional and Emerging Approaches to CO2 Reduction
Authors: Bell Jeffrey G. , Underwood Thomas C.
Published: January 2024

This perspective highlights unconventional and emerging approaches to CO2 reduction. These methods encompass the use of topological materials and 3D printing in electrochemistry and the broader fields of plasma- and magneto-electrochemistry. Sustainability in these methods offers a way to convert CO2 into value-added fuels in a circular energy economy. We identify challenges of reducing CO2 along sustainable pathways and detail ways that unconventional approaches can address these challenges. These include achieving high product selectivity toward desirable chemicals, high catalytic durability, high energy efficiency, and high conversion rates of CO2. Finally, we describe emerging impacts and opportunities of these unconventional approaches and key challenges.
Changes in Sustainable Development in Manufacturing in Cases of Unexpected Occurrences—A Systematic Review
Authors: Patalas-Maliszewska Justyna , Łosyk Hanna
Published: January 2024

Nowadays, managers are facing the challenge of operating in situations of high uncertainty: delayed deliveries, lack of energy or rising energy and gas costs, the need to replace energy sources, and changing supply and sales markets. In the literature, two dominant trends in the activities of enterprises in the face of crises can be distinguished: (I) changes in supply chain management (increased flexibility by searching for local suppliers); and (II) transition to digital production and investment in technologies in the concept of Industry 4.0 or even Industry 5.0, such as artificial intelligence, 3D printing, robots, cyber-physical systems, digital manufacturing, and blockchain. A gap in the research has been observed in examining the impacts of these actions on the implementation of sustainable solutions and designating organizational changes in manufacturing. The main goal of this study is to review the literature using the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) for data collection and, secondly, the methodology of Systematic Literature Review (SLR) and Mapping in Literature Reviews (MLR). Our literature review of the selected databases is based on 566 published articles in 2020–2022. The achieved results indicate the main organizational changes in the context of sustainable development in manufacturing, namely in the business management area (adopting Sustainable Project Management (SPM), Sustainable Supply Chain Management practices, Sustainable Supplier Selection (SSS), and Resilient Manufacturing Strategy (RMS)) and in the production area (adopting Internet of Things (IoT)-enabled Additive Manufacturing assists, simulation software, and Life Cycle Assessment. The findings of our study revealed key relationships between the adoption of fifth-generation industrial technologies and the sustainable development of manufacturing.
Warming Climate-Induced Changes in Lithuanian River Ice Phenology
Authors: Šarauskienė Diana , Jakimavičius Darius , Jurgelėnaitė Aldona , Kriaučiūnienė Jūratė
Published: January 2024

Due to rising surface air temperatures, river ice is shrinking dramatically in the Northern Hemisphere. Ice cover during the cold season causes fundamental changes in river ecosystems and has important implications for nearby communities and industries. Changes caused by climate warming, therefore, affect the sustainability of key resources, livelihoods, and traditional practices. Thus far, too little attention has been paid to research into the phenomenon of river ice in the Baltic States. Since the observational data of the last sixty years are currently available, we took advantage of the unique opportunity to assess ice regime changes in the gauged rivers by comparing two climatological standard normals. By applying statistical methods (Mann–Kendall, Pettitt, SNHT, Buishand, von Neumann, and Wilcoxon rank sum tests), this study determined drastic changes in ice phenology parameters (freeze-up date, ice break-up date, and ice cover duration) of Lithuanian rivers in the last thirty-year period. The dependence of the selected parameters on local climatic factors and large-scale atmospheric circulation patterns was identified. It was established that the sum of negative air temperatures, as well as the North Atlantic Oscillation, East Atlantic, and Arctic Oscillation indices, have the greatest influence on the ice regime of Lithuanian rivers.
Pricing Models under Three-Echelon Prefabricated Construction Supply Chains with Consumer Preferences
Authors: Jiang Wen , Hua Yichao , Yuan Meng , Martek Igor , Jiang Weiling
Published: January 2024

With the growing ecological crisis and consumer environmental awareness, there is a general recognition of the urgent need for the reform of the energy-intensive construction industry. Prefabricated construction has emerged as an effective approach to achieve energy conservation and environmental sustainability. The prefabricated rate is a critical indicator that comprehensively reflects the level of technology, which affects orders, costs, pricing, and partnerships. Moreover, given the highly decentralized nature of the construction industry, it is imperative to consider building materials’ supply in the Prefabricated Construction Supply Chain (PCSC). Therefore, this paper investigates how the prefabricated rate affects consumer preferences and order allocation while designing a three-echelon PCSC under a single-supplier structure, two-supplier structure, and dual-channel structure. Two different channels, prefabricated component and non-prefabricated component, are distinguished by the prefabricated rate. This research not only provides pricing-oriented decision advice but also offers suggestions for channel selection among participants. The results show that the increase in consumers’ preference for the prefabricated rate raises prices. Moreover, a moderate prefabricated rate is most beneficial. Comparing the three models, the supply chain performance of a two-supplier structure is better than that of a single-supplier structure if the prefabricated rate exceeds a certain threshold, while the dual-channel structure is the worst.
Research on the Spatial Dynamic Evolution of Digital Agriculture—Evidence from China
Authors: Meng Jiajia , Zhao Baoyu , Song Yuxiao , Lin Xiaomei
Published: January 2024

Digital agriculture serves as a pivotal means of ushering in innovative agricultural practices and achieving sustainable agricultural development. Although agricultural digitalization has received increasing attention, the unbalanced development and regional disparities of digital agriculture are still key obstacles to sustainable agricultural development. Based on the data of 31 provinces in China from 2013 to 2021, this study evaluates the development level of digital agriculture in China, and further analyzes the distribution pattern, spatial characteristics, and transition probabilities of digital agriculture from a regional perspective. The index system of the digital agriculture development level is constructed from five aspects: infrastructure, talent resources, agricultural informatization, the digitization of agricultural production processes, and agricultural production efficiency. Among these, infrastructure and talent resources reflect the resources needed for the development of digital agriculture; agricultural informatization and the digitization of the agricultural production process indicate the role of digitization in the process of agricultural development; and the agricultural production efficiency is the goal of the digital agriculture development, which is a critical criteria of its evaluation. The weighted analysis method of objective sequential analysis, which combines the dynamic level of indicators and sequential relationships, is used to assign weights to the indicators. In addition, to address the regional disparities in the development level of digital agriculture, kernel density estimation, Moran’s index, and (spatial) Markov chain analysis are applied to analyze the spatial dynamic evolution of digital agriculture in China. The findings reveal substantial regional disparities in digital agriculture development within China, particularly in the Western region, where development lags behind. Moreover, this study offers actionable policy recommendations for policymakers to strengthen regional infrastructure and talent cultivation, as well as other aspects of digital agriculture development, to mitigate regional differences and provide reference for other emerging countries.
Bioconversion of Agroindustrial Asparagus Waste into Bacterial Cellulose by Komagataeibacter rhaeticus
Authors: Quiñones-Cerna Claudio , Rodríguez-Soto Juan Carlos , Barraza-Jáuregui Gabriela , Huanes-Carranza Johnny , Cruz-Monzón José Alfredo , Ugarte-López Wilmer , Hurtado-Butrón Fernando , Samanamud-Moreno Fanny , Haro-Carranza David , Valdivieso-Moreno Stefany , Salirrosas-Fernández David , Quiñones Marisol Contreras
Published: January 2024

Bacterial cellulose is a biomaterial known for its physical and mechanical properties, including its high mechanical strength, water retention capacity, and biocompatibility. Its production from various carbohydrates has been widely studied, aiming to find more efficient and cost-effective culture media. This study investigated the production of bacterial cellulose from agroindustrial asparagus peel waste by Komagataeibacter rhaeticus QK23. A strain of QK23 was isolated and cultivated from a kombucha tea, identified based on morphological and molecular characteristics using the 16S rRNA gene. The waste was hydrolyzed and converted into fermentable sugars. Using the response surface methodology, the inoculum dose (1–20%) and incubation time (3–25 days) were evaluated concerning bacterial cellulose yield. The results demonstrated that with an optimal inoculum dose of 10.5% and an incubation time of 25 days, a production of 2.57 g/L was achieved. It was characterized as similar to type I cellulose, exhibiting a high degree of crystallinity (81.89%) and suitable morphological properties, evidenced by a fiber size of 178 nm and a surface roughness of 27.05 nm. Converting asparagus waste into bacterial cellulose is a sustainable and effective strategy that promotes the development of advanced biomaterials in biotechnology research.
A Modular IoT-Based Architecture for Logistics Service Performance Assessment and Real-Time Scheduling towards a Synchromodal Transport System
Authors: Brochado Ângela F. , Rocha Eugénio M. , Costa Diogo
Published: January 2024

Logistics is significantly impacted by quality/quantity issues associated with data collection and data sharing restrictions. Nonetheless, public data from national entities and internet-of-things (IoT) solutions enable the development of integrated tools for performance analysis and real-time optimization of logistics networks. This study proposes a three-module data-driven system architecture that covers (a) logistics data collection tools, (b) logistics services performance evaluation, and (c) the transition to synchromodal systems. Module 1 integrates multisource data from national logistics platforms and embedded devices placed within intermodal containers. A multigraph representation of the problem is conceived. Environmental, economic, and operational data are generated and injected into a digital twin. Thus, key performance indicators (KPIs) are computed by simulation or direct transformation of the collected data. Module 2 uses Multi-directional Efficiency Analysis, an optimization algorithm that benchmarks multimodal transportation routes of containers using prior KPIs. Outputs are a technical performance index relevant to logistics clients and improvement measures for logistics service providers. A real case study application of the solution proposed for Module 2 is presented. Module 3 provides real-time scheduling and assignment models using CP-sat solvers, accommodating varying system dynamics and resource availability, minimizing makespan and operational costs.
A New Symmetry-Enhanced Simulation Approach Considering Poromechanical Effects and Its Application in the Hydraulic Fracturing of a Carbonate Reservoir
Authors: Wang Chuanrui , Yue Yao , Huang Zhongkai , Tong Yue , Zhang Wei , Ye Shiying
Published: January 2024

The exploration of fractured-vuggy carbonate reservoirs usually involves hydraulic fracturing to maximize recovery. At present, effectively communicating natural discontinuities is a technical challenge. In this article, we investigated the origin and propagation of cracks in fractured-vuggy reservoirs using discrete element hydraulic fracturing simulations that included poromechanical effects. A particular focus on the microscopic force-displacement symmetry of adjacent pore pressures is introduced. Our results demonstrate that the poromechanical effect significantly increases the strength of overpressurized reservoir formations. Moreover, the effect of injected fluid viscosity on the hydraulic fracturing effectiveness was studied through two simulation tests. The outcomes highlight the critical influence of fluid viscosity on the propagation of micro-cracks in overpressure fractured-vuggy reservoirs.
Real-Time Exposure to 3D-Printing Emissions Elicits Metabolic and Pro-Inflammatory Responses in Human Airway Epithelial Cells
Authors: He Xiaojia , Barnett Lillie Marie , Jeon Jennifer , Zhang Qian , Alqahtani Saeed , Black Marilyn , Shannahan Jonathan , Wright Christa
Published: January 2024

Three-dimensional (3D) printer usage in household and school settings has raised health concerns regarding chemical and particle emission exposures during operation. Although the composition of 3D printer emissions varies depending on printer settings and materials, little is known about the impact that emissions from different filament types may have on respiratory health and underlying cellular mechanisms. In this study, we used an in vitro exposure chamber system to deliver emissions from two popular 3D-printing filament types, acrylonitrile butadiene styrene (ABS) and polylactic acid (PLA), directly to human small airway epithelial cells (SAEC) cultured in an air–liquid interface during 3D printer operation. Using a scanning mobility particle sizer (SMPS) and an optical particle sizer (OPS), we monitored 3D printer particulate matter (PM) emissions in terms of their particle size distribution, concentrations, and calculated deposited doses. Elemental composition of ABS and PLA emissions was assessed using scanning electron microscopy coupled with energy dispersive X-ray spectroscopy (SEM-EDX). Finally, we compared the effects of emission exposure on cell viability, inflammation, and metabolism in SAEC. Our results reveal that, although ABS filaments emitted a higher total concentration of particles and PLA filaments emitted a higher concentration of smaller particles, SAEC were exposed to similar deposited doses of particles for each filament type. Conversely, ABS and PLA emissions had distinct elemental compositions, which were likely responsible for differential effects on SAEC viability, oxidative stress, release of inflammatory mediators, and changes in cellular metabolism. Specifically, while ABS- and PLA-emitted particles both reduced cellular viability and total glutathione levels in SAEC, ABS emissions had a significantly greater effect on glutathione relative to PLA emissions. Additionally, pro-inflammatory cytokines including IL-1β, MMP-9, and RANTES were significantly increased due to ABS emissions exposure. While IL-6 and IL-8 were stimulated in both exposure scenarios, VEGF was exclusively increased due to PLA emissions exposures. Notably, ABS emissions induced metabolic perturbation on amino acids and energy metabolism, as well as redox-regulated pathways including arginine, methionine, cysteine, and vitamin B3 metabolism, whereas PLA emissions exposures caused fatty acid and carnitine dysregulation. Taken together, these results advance our mechanistic understanding of 3D-printer-emissions-induced respiratory toxicity and highlight the role that filament emission properties may play in mediating different respiratory outcomes.
Assessment of Essential and Potentially Toxic Elements in Water and Sediment and the Tissues of Sciaena deliciosa (Tschudi, 1846) from the Coast of Callao Bay, Peru
Authors: Guabloche Angélica , Alvariño Lorena , Acioly Thiago Machado da Silva , Viana Diego Carvalho , Iannacone José
Published: January 2024

The lorna drum Sciaena deliciosa is a coastal demersal species and one of the underlying artisanal fisheries in some areas of Peru, and is also a source of protein for Peruvian coastal dwellers. The investigation addresses concern about the environmental impact on this fish species and the potential risks to human health through the consumption of contaminated seafood. This research endeavors to assess the concentration of potentially toxic and essential elements in the muscle and liver tissues of S. deliciosa, in addition to the presence thereof in water and sediment capture areas on the coast of Callao, Peru. The study revealed that, in water samples, Ag, Ni, and Zn exceed Peruvian standards, but were below international standards, and Ba, P, Se, and Sn exceed international standards. In the sediments, As, Cd, Pb, Fe, and Zn were above international standards. In the fish, S. delicious muscle demonstrated As, Hg, and Pb exceeding at least one international standard. In the liver, As, Hg, Pb, and Cu exceed international standards. The study approach increased accuracy in risk assessments, offering crucial insights into the interplay between heavy metal pollution, water quality, and animal health, informing risk management strategies. Future studies can explore the long-term effects of heavy metal exposure on different organisms and consider their cumulative impact on health.
The Contribution of Microglia and Brain-Infiltrating Macrophages to the Pathogenesis of Neuroinflammatory and Neurodegenerative Diseases during TMEV Infection of the Central Nervous System
Authors: DePaula-Silva Ana Beatriz
Published: January 2024

The infection of the central nervous system (CNS) with neurotropic viruses induces neuroinflammation and is associated with the development of neuroinflammatory and neurodegenerative diseases, including multiple sclerosis and epilepsy. The activation of the innate and adaptive immune response, including microglial, macrophages, and T and B cells, while required for efficient viral control within the CNS, is also associated with neuropathology. Under healthy conditions, resident microglia play a pivotal role in maintaining CNS homeostasis. However, during pathological events, such as CNS viral infection, microglia become reactive, and immune cells from the periphery infiltrate into the brain, disrupting CNS homeostasis and contributing to disease development. Theiler’s murine encephalomyelitis virus (TMEV), a neurotropic picornavirus, is used in two distinct mouse models: TMEV-induced demyelination disease (TMEV-IDD) and TMEV-induced seizures, representing mouse models of multiple sclerosis and epilepsy, respectively. These murine models have contributed substantially to our understanding of the pathophysiology of MS and seizures/epilepsy following viral infection, serving as critical tools for identifying pharmacological targetable pathways to modulate disease development. This review aims to discuss the host–pathogen interaction during a neurotropic picornavirus infection and to shed light on our current understanding of the multifaceted roles played by microglia and macrophages in the context of these two complexes viral-induced disease.