bluuebunny/crossref_metadata_2025 huggingface dataset:
Study on Ratio Optimization and Diffusion-Gelation Process of Polymer Grouting Materials for Fracture Filling in Underground Mines
Authors: Zhang Xuanning , Wang Ende
Published: June 2024

The existence of fissures poses a serious threat to the safe production of underground mines, and this paper investigates a polymer grouting material for filling fissures in underground mines. To optimise the ratio of polymer grouting materials, this paper designed 16 test groups using the orthogonal test method to find the most reasonable slurry ratio. In order to study the gel diffusion process of polymer slurry in the fissure and to explore the changes of various parameters of the slurry after injection, simulated grouting tests were carried out, and the distribution laws of viscosity, pressure, and diffusion distance of the slurry were discussed. The findings indicate that when the proportion of ethylenediamine polypropylene oxide tetrol: glycerol polyether: catalyst: foam stabiliser is 10:8:0.5:0.4, the polymer grouting material has excellent compressive strength, and the maximum compressive strength can reach 12.31 MPa. Prior to reaching the gel time point, the viscosity of the polymer slurry was nearly constant, which is basically maintained at 0.772 Pa·s under normal temperature and pressure, but after reaching the gel time point, it abruptly rose. As the slurry mass increased, so did the penetration distance and pressure; in the simulated grouting test, when the slurry mass was 400 g, the maximum diffusion distance of the slurry reached 39 cm. Conversely, as the fracture pore size increased, the diffusion distance and pressure of the slurry decreased. Along the diffusion path, the slurry pressure progressively drops, but this change is not synchronised with the diffusion distance’s change. This work can serve as a reference for the configuration of polymer slurry and aid in comprehending the diffusion law of the slurry within the fissure.
Research on the Consistency Evaluation of the Spindle Unit Stiffness Based on Comprehensive Weights
Authors: Sun Feng , Jiang Yu , Zhou Ran , Zhang Qi , Xu Fangchao , Zhao Chuan , Zhao Haining , Yang Wenhua , Li Bo , Bai Shuang
Published: June 2024

The spindle unit is the core component of a machine, and its stiffness is a key performance characteristic. The stiffness consistency is a key index to measure the stiffness of spindle units; however, there is a lack of unified evaluation methods for the spindle unit stiffness consistency. This paper proposes a comprehensive method for the evaluation of the spindle unit stiffness consistency based on fluctuations and comprehensive weights. First, the consistency of the spindle unit stiffness evaluation indices is expressed based on the fluctuations. Secondly, the subjective and objective weights of the spindle unit stiffness evaluation indices are given based on the AHP and CRITIC weight assignment methods. To obtain the comprehensive weights of the evaluation indices, the subjective and objective weights are synthesized based on the linear weighting method. Then, the consistency level of the spindle unit stiffness is obtained by the weighted summation of the comprehensive weights and fluctuations of the evaluation indices. Finally, the stiffness consistency of a group of spindle units is evaluated based on this method, and the evaluation result shows a 10.63% fluctuation, which indicates that its stiffness consistency level is class B, in line with the factory production requirements.
Back to Basics: The Power of the Multilayer Perceptron in Financial Time Series Forecasting
Authors: Lazcano Ana , Jaramillo-Morán Miguel A. , Sandubete Julio E.
Published: June 2024

The economic time series prediction literature has seen an increase in research leveraging artificial neural networks (ANNs), particularly the multilayer perceptron (MLP) and, more recently, transformer networks. These ANN models have shown superior accuracy compared to traditional techniques such as autoregressive integrated moving average (ARIMA) models. The most recent models in the prediction of this type of neural network, such as recurrent or Transformers models, are composed of complex architectures that require sufficient processing capacity to address the problems, while MLP is based on densely connected layers and supervised learning. A deep understanding of the limitations is necessary to appropriately choose the ideal model for each of the prediction tasks. In this article, we show how a simple architecture such as the MLP allows a better adjustment than other models, including a shorter prediction time. This research is based on the premise that the use of the most recent models will not always allow better results.
Constructing Solutions to Multi-Term Cauchy–Euler Equations with Arbitrary Fractional Derivatives
Authors: Dubovski Pavel B. , Slepoi Jeffrey A.
Published: June 2024

We further extend the results of other researchers on existence theory to homogeneous fractional Cauchy–Euler equations ∑i=1mdixαiDαiu(x)+μu(x)=0,αi>0, with the derivatives in Caputo or Riemann–Liouville sense. Unlike the existing works, we consider multi-term equations without any restrictions on the order of fractional derivatives. The results are based on the characteristic equations which generate the solutions. Depending on the roots of the characteristic equations (real, multiple, or complex), we construct the corresponding solutions and prove their linear independence.
3D Vase Design Based on Interactive Genetic Algorithm and Enhanced XGBoost Model
Authors: Wang Dongming , Xu Xing
Published: June 2024

The human–computer interaction attribute of the interactive genetic algorithm (IGA) allows users to participate in the product design process for which the product needs to be evaluated, and requiring a large number of evaluations would lead to user fatigue. To address this issue, this paper utilizes an XGBoost proxy model modified by particle swarm optimization and the graphical interaction mechanism (GIM) to construct an improved interactive genetic algorithm (PXG-IGA), and then the PXG-IGA is applied to 3D vase design. Firstly, the 3D vase shape has been designed by using a bicubic Bézier surface, and the individual genetic code is binary and includes three parts: the vase control points, the vase height, and the texture picture. Secondly, the XGBoost evaluation of the proxy model has been constructed by collecting user online evaluation data, and the particle swarm optimization algorithm has been used to optimize the hyperparameters of XGBoost. Finally, the GIM has been introduced after several generations, allowing users to change product styles independently to better meet users’ expectations. Based on the PXG-IGA, an online 3D vase design platform has been developed and compared to the traditional IGA, KD tree, random forest, and standard XGBoost proxy models. Compared with the traditional IGA, the number of evaluations has been reduced by 58.3% and the evaluation time has been reduced by 46.4%. Compared with other proxy models, the accuracy of predictions has been improved up from 1.3% to 20.2%. To a certain extent, the PXG-IGA reduces users’ operation fatigue and provides new ideas for improving user experience and product design efficiency.
Reconstructing the Colors of Underwater Images Based on the Color Mapping Strategy
Authors: Wu Siyuan , Sun Bangyong , Yang Xiao , Han Wenjia , Tan Jiahai , Gao Xiaomei
Published: June 2024

Underwater imagery plays a vital role in ocean development and conservation efforts. However, underwater images often suffer from chromatic aberration and low contrast due to the attenuation and scattering of visible light in the complex medium of water. To address these issues, we propose an underwater image enhancement network called CM-Net, which utilizes color mapping techniques to remove noise and restore the natural brightness and colors of underwater images. Specifically, CM-Net consists of a three-step solution: adaptive color mapping (ACM), local enhancement (LE), and global generation (GG). Inspired by the principles of color gamut mapping, the ACM enhances the network’s adaptive response to regions with severe color attenuation. ACM enables the correction of the blue-green cast in underwater images by combining color constancy theory with the power of convolutional neural networks. To account for inconsistent attenuation in different channels and spatial regions, we designed a multi-head reinforcement module (MHR) in the LE step. The MHR enhances the network’s attention to channels and spatial regions with more pronounced attenuation, further improving contrast and saturation. Compared to the best candidate models on the EUVP and UIEB datasets, CM-Net improves PSNR by 18.1% and 6.5% and SSIM by 5.9% and 13.3%, respectively. At the same time, CIEDE2000 decreased by 25.6% and 1.3%.
Fuzzy Evaluation Model for Lifetime Performance Using Type-I Censoring Data
Authors: Chiou Kuo-Ching , Huang Tsun-Hung , Chen Kuen-Suan , Yu Chun-Min
Published: June 2024

As global warming becomes increasingly serious, humans start to consider how to coexist with the natural environment. People become more and more aware of environmental protection and sustainable development. Therefore, in the pursuit of economic growth, it has become a consensus that enterprises should be responsible for the social and ecological environment. Regarding the manufacturing of electronic devices, as long as both component production quality and assembly quality are ensured, consumers can be provided with high-quality, safe, and efficient products. In light of this trend, enhancing product availability and reliability can reduce costs and carbon emissions resulting from repairing or replacing components, thus becoming a vital factor for corporate and environmental sustainability. Accordingly, enterprises enhance their economic benefits as well as have the effects of energy conservation and waste reduction by extending products’ service lifetime and increasing their added value. According to several studies, it takes a long time to retrieve electronic products’ lifetime data. Moreover, acquiring complete samples is often challenging. Consequently, when analyzing real cases, samples are usually collected using censoring techniques. The type-I right censoring data is suitable for industrial processes. Thus, this study utilized type-I right censoring sample data to estimate the lifetime performance index. It usually takes a large amount of time to access lifetime data for electronic products and it is often impossible to obtain complete samples since the size of the sample is usually small. Hence, to avoid misjudgment caused by sampling errors, this study followed suggestions from existing research and applied fuzzy tests built on confidence intervals to establish a fuzzy evaluation model for the lifetime performance index. This model helps relevant electronic industries not only evaluate the lifetime of their electronic components but also instantly seize opportunities for improvement.
Effects of Marine Natural Products on Liver Diseases
Authors: Sun Yandi , Dong Yansong , Cui Xiaohang , Guo Xiaohe , Zhang Juan , Yu Chong , Zhang Man , Wang Haifeng
Published: June 2024

The prevention and treatment of liver disease, a class of disease that seriously threatens human health, has always been a hot topic of medical research. In recent years, with the in-depth exploration of marine resources, marine natural products have shown great potential and value in the field of liver disease treatment. Compounds extracted and isolated from marine natural products have a variety of biological activities such as significant antiviral properties, showing potential in the management of alcoholic liver disease (ALD) and non-alcoholic fatty liver disease (NAFLD), protection of the liver from fibrosis, protection from liver injury and inhibition of the growth of hepatocellular carcinoma (HCC). This paper summarizes the progress of research on marine natural products for the treatment of liver diseases in the past decade, including the structural types of active substances from different natural products and the mechanisms underlying the modulation of different liver diseases and reviews their future prospects.
Sustainable Remediation of Soil and Water Utilizing Arbuscular Mycorrhizal Fungi: A Review
Authors: Zhang Xueqi , Wang Zongcheng , Lu Yebin , Wei Jun , Qi Shiying , Wu Boran , Cheng Shuiping
Published: June 2024

Phytoremediation is recognized as an environmentally friendly technique. However, the low biomass production, high time consumption, and exposure to combined toxic stress from contaminated media weaken the potential of phytoremediation. As a class of plant-beneficial microorganisms, arbuscular mycorrhizal fungi (AMF) can promote plant nutrient uptake, improve plant habitats, and regulate abiotic stresses, and the utilization of AMF to enhance phytoremediation is considered to be an effective way to enhance the remediation efficiency. In this paper, we searched 520 papers published during the period 2000–2023 on the topic of AMF-assisted phytoremediation from the Web of Science core collection database. We analyzed the author co-authorship, country, and keyword co-occurrence clustering by VOSviewer. We summarized the advances in research and proposed prospective studies on AMF-assisted phytoremediation. The bibliometric analyses showed that heavy metal, soil, stress tolerance, and growth promotion were the research hotspots. AMF–plant symbiosis has been used in water and soil in different scenarios for the remediation of heavy metal pollution and organic pollution, among others. The potential mechanisms of pollutant removal in which AMF are directly involved through hyphal exudate binding and stabilization, accumulation in their structures, and nutrient exchange with the host plant are highlighted. In addition, the tolerance strategies of AMF through influencing the subcellular distribution of contaminants as well as chemical form shifts, activation of plant defenses, and induction of differential gene expression in plants are presented. We proposed that future research should screen anaerobic-tolerant AMF strains, examine bacterial interactions with AMF, and utilize AMF for combined pollutant removal to accelerate practical applications.
Molecular Mechanisms of Bacterial Resistance to Antimicrobial Peptides in the Modern Era: An Updated Review
Authors: Tajer Layla , Paillart Jean-Christophe , Dib Hanna , Sabatier Jean-Marc , Fajloun Ziad , Abi Khattar Ziad
Published: June 2024

Antimicrobial resistance (AMR) poses a serious global health concern, resulting in a significant number of deaths annually due to infections that are resistant to treatment. Amidst this crisis, antimicrobial peptides (AMPs) have emerged as promising alternatives to conventional antibiotics (ATBs). These cationic peptides, naturally produced by all kingdoms of life, play a crucial role in the innate immune system of multicellular organisms and in bacterial interspecies competition by exhibiting broad-spectrum activity against bacteria, fungi, viruses, and parasites. AMPs target bacterial pathogens through multiple mechanisms, most importantly by disrupting their membranes, leading to cell lysis. However, bacterial resistance to host AMPs has emerged due to a slow co-evolutionary process between microorganisms and their hosts. Alarmingly, the development of resistance to last-resort AMPs in the treatment of MDR infections, such as colistin, is attributed to the misuse of this peptide and the high rate of horizontal genetic transfer of the corresponding resistance genes. AMP-resistant bacteria employ diverse mechanisms, including but not limited to proteolytic degradation, extracellular trapping and inactivation, active efflux, as well as complex modifications in bacterial cell wall and membrane structures. This review comprehensively examines all constitutive and inducible molecular resistance mechanisms to AMPs supported by experimental evidence described to date in bacterial pathogens. We also explore the specificity of these mechanisms toward structurally diverse AMPs to broaden and enhance their potential in developing and applying them as therapeutics for MDR bacteria. Additionally, we provide insights into the significance of AMP resistance within the context of host–pathogen interactions.
Thanos: An R Package for the Gene-Centric Analysis of Functional Potential in Metagenomic Samples
Authors: Zhao Zhe , Marotta Federico , Wu Min
Published: June 2024

As the amount of metagenomic sequencing continues to increase, there is a growing need for tools that help biologists make sense of the data. Specifically, researchers are often interested in the potential of a microbial community to carry out a metabolic reaction, but this analysis requires knitting together multiple software tools into a complex pipeline. Thanos offers a user-friendly R package designed for the pathway-centric analysis and visualization of the functions encoded within metagenomic samples. It allows researchers to go beyond taxonomic profiles and find out, quantitatively, which pathways are prevalent in an environment, as well as comparing different environments in terms of their functional potential. The analysis is based on the sequencing depth of the genes of interest, either in the metagenome-assembled genomes (MAGs) or in the assembled reads (contigs), using a normalization strategy that enables comparison across samples. The package can import the data from multiple formats and offers functions for the visualization of the results as bar plots of the functional profile, box plots of compare functions across samples, and annotated pathway graphs. By streamlining the analysis of the functional potential encoded in microbial communities, Thanos can enable impactful discoveries in all the fields touched by metagenomics, from human health to the environmental sciences.
Synthesis and Biological Evaluation of Novel Biased Mu-Opioid Receptor Agonists
Authors: Guo Yanhao , Yu Ruimin , Zhang Tao , Ren Fengxia , Yu Zixing , Cheng Jingchao , Jia Hongxin , Shi Weiguo , Zhang Yatong
Published: June 2024

This study explored the potential of a series of PZM21 analogues for pain treatment. Specifically, the hydroxyphenyl ring of PZM21 was replaced with a naphthyl ring, the thienyl ring was substituted with either a phenyl ring or furan rings, and the essential dimethylamine and urea groups were retained. These compounds aimed to enhance safety and minimize the adverse effects associated with opioid drugs. The research findings suggest that compound 6a does not induce β-arrestin recruitment at low-nanomolar concentrations but exhibits significant analgesic effects in established mouse models. Compared to morphine, 6a shows advantages in alleviating respiratory depression and minimizing physical dependence. Molecular docking studies underscore the pivotal role of the D147 amino acid residue in the analgesic mechanism of 6a. Consequently, 6a is a compelling candidate for the development of safer opioid analgesics and warrants further attention.
Engaging in Action Research with Nurses: Overcoming Challenges and Gaining Positive Insights into End-of-Life Care
Authors: Oura Yuka , Kato Shiori , Kaino Risa , Sato Yasuna , Shida Junko , Uno Chisaki , Matsuda Yumi
Published: June 2024

The aim of this study was to qualitatively describe, from a practitioner’s perspective, the process by which nurses struggle to support a patient with end-of-life cancer with frequent nurse calls and gain positive insights through two methodologies: AR and the case study method. The participants were four ward nurses who supported a patient receiving end-of-life cancer in his 80s. The participants engaged in monthly group work and practical training sessions, which included facilitators, to reflect on and develop care plans. Based on these activities, care was provided to the patient. After the intervention period, the patient’s course and practice was documented and analysed qualitatively. The intervention significantly improved the nurses’ ability to support inpatients with many needs through careful observation, enhancement, and practical skill improvement. This process resulted in a better understanding of patient needs, proactive skill development, enhanced team performance, and an innovative care-delivery system that resonated throughout the ward. This study demonstrated a successful strategy for nurses to improve support for high-need inpatients, emphasising the importance of attentive care, proactive skill improvement, and a team-based approach to healthcare innovation.
Going High to Keep Body Mass Low: How Post-Exercise Exposure to a Simulated High Altitude Influences Energy Balance—A Proof-of-Concept Pilot Study
Authors: Allen Peyton E. , Akinwumi Akinola D. , Kroeze Evan G. , Leigh Paula Y. , Ramirez Sahnet N. , Smart Gregory L. , Thomas Tay M. , Paris Hunter L.
Published: June 2024

A healthy body mass contributes to a positive quality of life, and for overweight/obese individuals, weight loss of even modest proportions improves health-related outcomes. A novel approach to promoting body mass regulation is to pair exercise with high altitude, thereby upregulating metabolic processes and increasing caloric expenditure. As an added measure of body mass regulation, data suggest that high altitude stimulates the production of the appetite-suppressing hormone leptin. Issues arise, however, given that high altitude compromises aerobic exercise capacity. Whereas exercising at high altitude may compromise exercise intensity and duration, recovering at high altitude retains the integrity of exercise while still potentially conferring the benefits of the low oxygen environment on energy expenditure and energy intake. The purpose of this study was to perform a proof-of-concept pilot test on whether post-exercise exposure to a simulated high altitude influenced acute energy balance. Twelve healthy men and women ran for 30 min at a moderate intensity on two separate occasions. Following exercise, participants recovered for 30 min while breathing either sea level air or low oxygen air simulating high altitude (equivalent to 4500 m elevation). Blood samples and hunger ratings were collected pre-exercise and post-recovery. Heart rate was recorded throughout exercise and recovery and used to calculate caloric expenditure. Post-exercise energy expenditure was significantly higher (p = 0.03) following high altitude recovery (139 ± 15 kcal) compared to sea-level recovery (98 ± 11 kcal). Participants reported a lower desire to eat when they recovered in the high altitude environment (p = 0.01), though post-recovery leptin concentrations were similar between the two conditions. Post-exercise exposure to a simulated high altitude environment represents a promising method for increasing daily caloric expenditure and lowering appetite. Given the pilot nature of this study, future research is needed to address the question of high altitude recovery on a larger sample over a longer time period and with robust measures of caloric expenditure.
The Perception of God through Light in Plato and Dionysius the Areopagite
Authors: Laparidis Konstantinos
Published: June 2024

This article explores the soul’s capacity to see God. This is the process by which a human subject can apprehend and define the nature of God on a philosophical and theological level. Two conceptually very close philosophers, Plato and Dionysius the Areopagite (pseudo-Dionysius), highlighted this metaphysical function. The article will look into light as a concept of the mind and an expression of God’s nature. For Plato, God is the visible light, whereas for Areopagite, it is the invisible light. At the conceptual level, “God” will eventually combine the Platonic (Form of) Good(ness), or the “Good”, with the Christian God, perceived and defined as Goodness, beauty, perfection, and virtue. In attempting to know God, the soul follows an ascending or descending path, and the concept of negation will play a crucial role in this metaphysical and theological function. It will eventually be shown that the Good is the essence of God and, at the same time, what defines his unique singularity.
Elements of a First-Person Ecology: Historical Roots, Recognition and Ecospirituality
Authors: Arcos Esteban , Delorme Damien , Hess Gérald
Published: June 2024

Starting from the observation that there is a gap between knowledge of the environmental sciences and practical engagement, for example, in climate change or biodiversity loss, this article explores one possible explanation for this situation—namely, the process of objectification inherent in science. It then proposes to remedy the situation by defending the idea of a ‘first-person ecology’. This term refers to a field of research and practice that looks at the relationship between humans and nature from the point of view of the embodied and situated nature of lived experience. The lived experience of nature at the heart of a first-person ecology is first studied from an epistemic perspective using the concept of recognition, inspired by the Frankfurt School philosopher and sociologist Axel Honneth. It is then approached from a phenomenological perspective, using the emerging field of ecospirituality to describe the characteristics of this experience.
Techno-Economic Assessment of Municipal Solid Waste (MSW) Incineration in Ghana
Authors: Yakah Noah , Kwarteng Augustine Akuoko , Addy Cyrus , Yirenkyi Michael , Martin Andrew , Simons Anthony
Published: June 2024

Waste incineration with energy recovery is a matured Waste-to-Energy (WtE) technology which has contributed immensely to the disposal and management of Municipal Solid Waste (MSW) in industrialised nations. The adoption of this technology in developing countries is currently gaining momentum due to the numerous benefits that can be derived from its use. In this study, a techno-economic assessment of MSW incineration in proposed waste incineration facilities for use in Ghana was carried out. The technical assessment was conducted by determining the plant capacity and annual electricity production based on the combustible residues of MSW collected from various population sizes in the country, while the economic assessment was carried out by determining two key economic indicators, Net Present Value (NPV) and Levelised Cost of Energy (LCOE). It was found that a total of about 400 MW of electricity can be generated from the total of about 14,000 tonnes of MSW generated in the country daily. The NPV for a 35.81 MW installed capacity of waste incineration facility was found to be USD 166,410,969.24. However, the LCOE for the 35.81 MW capacity and all others considered was greater than the tariff of electricity for their respective capacities, which means waste incineration facilities are not economically viable ventures in Ghana. The implementation of these facilities in the country would, therefore, need governmental support in the form of subsidies and tax rebates. Three locations were proposed for the piloting of waste incineration facilities in the country, and these locations are in the Accra Metropolitan, Asokore-Mampong Metropolitan, and Sekondi-Takoradi Metropolitan Assemblies.
Simulation Research on Cylinder Liner Shape and Position Tolerance under Thermo-Mechanical Load
Authors: Han Feng , Wang Hui , Wang Jian , Wang Jingchao , Lin Jiewei , Dai Huwei , Zhang Junhong
Published: June 2024

The cylinder liner bears alternating thermal load and mechanical load, and evaluating the cylinder liner deformation is a key issue in the design stage of an engine. In this work, the shape and position tolerance of the cylinder liner to various loads were studied based on the finite element method, the simplex algorithm and the least square method. Firstly, the heat transfer boundary conditions of the cylinder liner were obtained through combustion simulation. Combined with the mechanical load, the transient deformation of the cylinder liner under the thermo-mechanical load was obtained. Subsequently, the out-of-roundness and coaxiality were selected to evaluate the shape and position changes in the cylinder liner. Finally, the transient tolerance analysis of the cylinder liner under alternating thermo-mechanical load was carried out. The results show that the maximum out-of-roundness of the cylinder liner under thermal load, mechanical load and thermos-mechanical load was 15.12, 43.40 and 51.76 μm, respectively. The maximum coaxiality under thermal load, mechanical load and thermos-mechanical load were 6.17, 80.49 and 80.22 μm. The side thrust was more likely to cause uneven deformation of the cylinder liner section, the liner coaxiality was mainly affected by the cylinder burst pressure, and the liner shape tolerance was much more sensitive to the mechanical load than the mechanical load.
Decomposition of Organic Pollutants in Subcritical Water under Moderate Conditions
Authors: Švarc-Gajić Jaroslava , Brezo-Borjan Tanja , Jakšić Sandra , Despotović Vesna , Finčur Nina , Bognár Szabolcs , Jovanović Dušica , Šojić Merkulov Daniela
Published: June 2024

In this research, the efficiency of degradation of different organic contaminant classes, including pesticides (tembotrione, clomazone), pharmaceuticals (ciprofloxacin, 17α-ethinyl estradiol) and mycotoxins (zearalenone, deoxynivalenol, fumonisin B1) with subcritical water treatment was studied in model systems. All experiments were conducted in a house-made batch-type pilot reactor. The research was focused on the optimization of the treatment parameters using moderate treatment conditions. Optimization of the remediation processes of water contaminated with 17α-ethinyl estradiol, tembotrione, clomazone, and ciprofloxacin, was conducted through testing with different homogeneous and heterogeneous catalysts, as well as different gas atmospheres (nitrogen and carbon dioxide) for pressurization of the process system. Mycotoxins in water were degraded without catalysts and all experiments were conducted in nitrogen atmosphere. Optimization was conducted through defining the optimal combination of the treatment temperature and time, oriented towards energy saving and minimization of the technical requirements. The degradation efficiency in all tested samples was determined via HPLC analysis. Study showed the full degradation of tembotrione and all tested mycotoxins at 200 °C without a need for a catalyst. The efficiency of degradation of other tested pollutants at 200 °C was satisfying and within the range of 89.5% (clomazone) to 98.7% (17α-ethinyl estradiol).
Biblical Hermeneutics without Interpretation? After Affect, beyond Representation, and Other Minor Apocalypses
Authors: Moore Stephen D.
Published: June 2024

Affect theory, non-representational theory, and assemblage theory have been among the most impactful developments in the theoretical humanities in the wake of, and in reaction to, poststructuralism. These interlocking bodies of theory and critical practice call into question two concepts foundational for biblical hermeneutics, namely, interpretation and representation. In literary studies, the poststructuralist “death of the author” has been succeeded by a post-poststructuralist “death of the interpreter”. How might biblical exegesis be reimagined on the far side of this double demise? Non-representational theory, meanwhile, in tandem with affect theory, has dismantled traditional understandings of representation; this article argues that traditional biblical scholarship, epitomized by biblical commentary, is driven by a representation compulsion. Assemblage theory, for its part, more than any other body of thought, reveals the immense complexity of the act of reading, not least biblical reading—after which even explicit evocations of contemporary contexts in contextual biblical hermeneutics amount to skeletally thin descriptions. These and other related lines of inquiry impel the rethinking of academic biblical reading attempted in this article.
A Method of Precise Auto-Calibration in a Micro-Electro-Mechanical System Accelerometer
Authors: Łuczak Sergiusz , Ekwińska Magdalena , Tomaszewski Daniel
Published: June 2024

A novel design of a MEMS (Micro-Electromechanical System) capacitive accelerometer fabricated by surface micromachining, with a structure enabling precise auto-calibration during operation, is presented. Precise auto-calibration was introduced to ensure more accurate acceleration measurements compared to standard designs. The standard mechanical structure of the accelerometer (seismic mass integrated with elastic suspension and movable plates coupled with fixed plates forming a system of differential sensing capacitors) was equipped with three movable detection electrodes coupled with three fixed electrodes, thus creating three atypical tunneling displacement transducers detecting three specific positions of seismic mass with high precision, enabling the auto-calibration of the accelerometer while it was being operated. Auto-calibration is carried out by recording the accelerometer indication while the seismic mass occupies a specific position, which corresponds to a known value of acting acceleration determined in a pre-calibration process. The diagram and the design of the mechanical structure of the accelerometer, the block diagram of the electronic circuits, and the mathematical relationships used for auto-calibration are presented. The results of the simulation studies related to mechanical and electric phenomena are discussed.
An Integrated LSTM-Rule-Based Fusion Method for the Localization of Intelligent Vehicles in a Complex Environment
Authors: Yuan Quan , Yan Fuwu , Yin Zhishuai , Lv Chen , Hu Jie , Li Yue , Wang Jinhai
Published: June 2024

To improve the accuracy and robustness of autonomous vehicle localization in a complex environment, this paper proposes a multi-source fusion localization method that integrates GPS, laser SLAM, and an odometer model. Firstly, fuzzy rules are constructed to accurately analyze the in-vehicle localization deviation and confidence factor to improve the initial fusion localization accuracy. Then, an odometer model for obtaining the projected localization trajectory is constructed. Considering the high accuracy of the odometer’s projected trajectory within a short distance, we used the shape of the projected localization trajectory to inhibit the initial fusion localization noise and used trajectory matching to obtain an accurate localization. Finally, the Dual-LSTM network is constructed to predict the localization and build an electronic fence to guarantee the safety of the vehicle while also guaranteeing the updating of short-distance localization information of the vehicle when the above-mentioned fusion localization is unreliable. Under the limited arithmetic condition of the vehicle platform, accurate and reliable localization is realized in a complex environment. The proposed method was verified by long-time operation on the real vehicle platform, and compared with the EKF fusion localization method, the average root mean square error of localization was reduced by 66%, reaching centimeter-level localization accuracy.
Robots as Mental Health Coaches: A Study of Emotional Responses to Technology-Assisted Stress Management Tasks Using Physiological Signals
Authors: Klęczek Katarzyna , Rice Andra , Alimardani Maryam
Published: June 2024

The current study investigated the effectiveness of social robots in facilitating stress management interventions for university students by evaluating their physiological responses. We collected electroencephalogram (EEG) brain activity and Galvanic Skin Responses (GSRs) together with self-reported questionnaires from two groups of students who practiced a deep breathing exercise either with a social robot or a laptop. From GSR signals, we obtained the change in participants’ arousal level throughout the intervention, and from the EEG signals, we extracted the change in their emotional valence using the neurometric of Frontal Alpha Asymmetry (FAA). While subjective perceptions of stress and user experience did not differ significantly between the two groups, the physiological signals revealed differences in their emotional responses as evaluated by the arousal–valence model. The Laptop group tended to show a decrease in arousal level which, in some cases, was accompanied by negative valence indicative of boredom or lack of interest. On the other hand, the Robot group displayed two patterns; some demonstrated a decrease in arousal with positive valence indicative of calmness and relaxation, and others showed an increase in arousal together with positive valence interpreted as excitement. These findings provide interesting insights into the impact of social robots as mental well-being coaches on students’ emotions particularly in the presence of the novelty effect. Additionally, they provide evidence for the efficacy of physiological signals as an objective and reliable measure of user experience in HRI settings.
Development of a Dynamically Re-Configurable Radio-Frequency Interference Detection System for L-Band Microwave Radiometers
Authors: Perez-Portero Adrian , Querol Jorge , Mas-Vinolas Andreu , Amezaga Adria , Jove-Casulleras Roger , Camps Adriano
Published: June 2024

Real-Time RFI Detection and Flagging (RT-RDF) for microwave radiometers is a versatile new FPGA algorithm designed to detect and flag Radio-Frequency Interference (RFI) in microwave radiometers. This block utilizes computationally-efficient techniques to identify and analyze RF signals, allowing the system to take appropriate measures to mitigate interference and maintain reliable performance. With L-Band microwave radiometry as the main application, this RFI detection algorithm focuses on the Kurtogram and Spectrogram to detect non-Gaussian behavior. To gain further modularity, an FFT-based filter bank is used to divide the receiver’s bandwidth into several sub-bands within the band of interest of the instrument, depending on the application. Multiple blanking strategies can then be applied in each band using the provided detection flags. The algorithm can be re-configured in the field, for example with dynamic integration times to support operation in different environments, or configurable thresholds to account for variable RFI environments. A validation and testing campaign has been performed on multiple scenarios with the ARIEL commercial microwave radiometer, and the results confirm the excellent performance of the system.
Integration of Finite Element Analysis and Laboratory Analysis on 3D Models for Methodology Calibration
Authors: Gonizzi Barsanti Sara , De Finis Rosa , Nobile Riccardo
Published: June 2024

To better address mechanical behavior, it is necessary to make use of modern tools through which it is possible to run predictions, simulate scenarios, and optimize decisions. sources integration. This will increase the capability of detecting material modifications that forerun damage and/or to forecast the stage in the future when very likely fatigue is initiating and propagating cracks. Early warning outcomes obtained by the synergetic implementation of NDE-based protocols for studying mechanical and fatigue and fracture behavior will enhance the preparedness toward economically sustainable future damage control scenarios. Specifically, these early warning outcomes will be developed in the form of retopologized models to be used coupled with FEA. This paper presents the first stage of calibration and the combination of a system of different sensors (photogrammetry, laser scanning and strain gages) for the creation of volumetric models suitable for the prediction of failure of FEA software. The test objects were two components of car suspension to which strain gauges were attached to measure its deformation under cyclic loading. The calibration of the methodology was carried out using models obtained from photogrammetry and experimental strain gauge measurements.
Data Evaluation of a Low-Cost Sensor Network for Atmospheric Particulate Matter Monitoring in 15 Municipalities in Serbia
Authors: Stojanović Danka B. , Kleut Duška , Davidović Miloš , Živković Marija , Ramadani Uzahir , Jovanović Maja , Lazović Ivan , Jovašević-Stojanović Milena
Published: June 2024

Conventional air quality monitoring networks typically tend to be sparse over areas of interest. Because of the high cost of establishing such monitoring systems, some areas are often completely left out of regulatory monitoring networks. Recently, a new paradigm in monitoring has emerged that utilizes low-cost air pollution sensors, thus making it possible to reduce the knowledge gap in air pollution levels for areas not covered by regulatory monitoring networks and increase the spatial resolution of monitoring in others. The benefits of such networks for the community are almost self-evident since information about the level of air pollution can be transmitted in real time and the data can be analysed immediately over the wider area. However, the accuracy and reliability of newly produced data must also be taken into account in order to be able to correctly interpret the results. In this study, we analyse particulate matter pollution data from a large network of low-cost particulate matter monitors that was deployed and placed in outdoor spaces in schools in central and western Serbia under the Schools for Better Air Quality UNICEF pilot initiative in the period from April 2022 to June 2023. The network consisted of 129 devices in 15 municipalities, with 11 of the municipalities having such extensive real-time measurements of particulate matter concentration for the first time. The analysis showed that the maximum concentrations of PM2.5 and PM10 were in the winter months (heating season), while during the summer months (non-heating season), the concentrations were several times lower. Also, in some municipalities, the maximum values and number of daily exceedances of PM10 (50 μg/m3) were much higher than in the others because of diversity and differences in the low-cost sensor sampling sites. The particulate matter mass daily concentrations obtained by low-cost sensors were analysed and also classified according to the European AQI (air quality index) applied to low-cost sensor data. This study confirmed that the large network of low-cost air pollution sensors can be useful in providing real-time information and warnings about higher pollution days and episodes, particularly in situations where there is a lack of local or national regulatory monitoring stations in the area.
“Emergency Decisions”: The Choice of a Simulated Emergency Scenario to Reproduce a Decision-Making Condition in an Emergency Context as Close to Reality as Possible
Authors: D’Alessio Ivan
Published: June 2024

Decisions are a crucial aspect of human life, especially when made in emergency contexts. This research involved 348 subjects, evaluating the relationship between socio-demographic variables and the choice of one of the proposed emergency scenarios suitable for reproducing a decision-making condition in an emergency. Three scenarios were presented: one on climate change, one on pandemics, and one on seismic events. The survey captured individuals’ perceptions of the scenarios for dimensions such as realism (present, past, and future), emotions, risk, worry, emergency, catastrophe, immediate choice, and immediate decision. The results suggest that age, gender, education, and previous experience are predictive factors for subjects’ preferences regarding the chosen scenario and their evaluation of the related dimensions. To optimize decisions in emergencies by institutional decision makers and crisis managers, it is useful to expand knowledge and have data relevant to this area. This research provides a basis in terms of data and tools for designing future research and studies on decision making in emergency contexts.
Comment on Trotsenko et al. Early Results after Thulium Laser Enucleation of the Prostate in Patients with Urodynamically Proven Detrusor Underactivity. Soc. Int. Urol. J. 2024, 5, 160–168
Authors: Xu Perry , Krambeck Amy
Published: June 2024

In this study, AEEP (anatomical enucleation of the prostate) with a thulium laser was performed in 115 men at a single institution between January 2019 and March 2022 for surgical treatment of lower urinary tract symptoms (LUTS) secondary to benign prostatic hyperplasia (BPH) [...]
COVID-19 Booster Vaccination Status and Long COVID in the United States: A Nationally Representative Cross-Sectional Study
Authors: Romeiser Jamie L. , Schoeneck Kelsey
Published: June 2024

Early studies have found that the initial COVID-19 vaccination series was protective against severe symptoms and long COVID. However, few studies have explored the association of booster doses on severe disease outcomes and long COVID. This cross-sectional analysis used data from the 2022 US National Health Interview Survey data to investigate how vaccination status correlates with COVID-19 infection severity and long COVID among previously infected individuals. Participants were categorized into three groups: those who had received at least one booster, those with only the initial complete vaccination series, and those with either an incomplete series or no vaccinations. Out of 9521 survey respondents who reported a past positive COVID-19 test, 51.2% experienced moderate/severe infections, and 17.6% experienced long COVID. Multivariable regression models revealed that receiving at least one booster shot was associated with lower odds of experiencing moderate/severe symptoms (aOR = 0.78, p < 0.001) compared to those unvaccinated or with an incomplete series. Additionally, having at least one booster reduced long COVID odds by 24% (aOR = 0.76, p = 0.003). Completing only the primary vaccine series did not significantly decrease the likelihood of severe illness or long COVID. These findings support the continued promotion of booster vaccinations to mitigate long COVID risks in vulnerable populations.
Vaccination with a Human Papillomavirus L2 Multimer Provides Broad Protection against 17 Human Papillomavirus Types in the Mouse Cervicovaginal Challenge Model
Authors: Han Zhenwei , Wang Shen , Mu Ting , Zhao Ping , Song Lingli , Zhang Ying , Zhao Jin , Yin Wen , Wu Yue , Wang Huan , Gong Bo , Ji Min , Roden Richard B. S. , Yang Yanping , Klein Michel , Wu Ke
Published: June 2024

Human papillomavirus (HPV) is a prevalent cause of mucosal and cutaneous infections and underlying conditions ranging from benign warts to anogenital and oropharyngeal cancers affecting both males and females, notably cervical cancer. Cervical cancer is the fourth leading cause of cancer deaths among women globally and is the most impactful in low- and middle-income countries (LMICs), where the costs of screening and licensed L1-based HPV vaccines pose significant barriers to comprehensive administration. Additionally, the licensed L1-based HPV vaccines fail to protect against all oncogenic HPV types. This study generated three independent lots of an L2-based target antigen (LBTA), which was engineered from conserved linear L2-protective epitopes (aa11–88) from five human alphapapillomavirus genotypes in E. coli under cGMP conditions and adjuvanted with aluminum phosphate. Vaccination of rabbits with LBTA generated high neutralizing antibody titers against all 17 HPV types tested, surpassing the nine types covered by Gardasil®9. Passive transfer of naïve mice with LBTA antiserum revealed its capacity to confer protection against vaginal challenge with all 17 αHPV types tested. LBTA shows stability at room temperature over >1 month. Standard in vitro and in vivo toxicology studies suggest a promising safety profile. These findings suggest LBTA’s promise as a next-generation vaccine with comprehensive coverage aimed at reducing the economic and healthcare burden of cervical and other HPV+ cancers in LMICs, and it has received regulatory approval for a first-in-human clinical study (NCT05672966).