bluuebunny/crossref_metadata_2025 huggingface dataset:
Stability Evaluation of a Simplified Reclaimer Using Fluid–Structure Interaction
Authors: Januário João Rodolfo , Landre Júnior Janes , Maia Cristiana Brasil
Published: March 2024

This paper describes the numerical modeling and simulation of the wind effects on an ore reclaimer structure using analytical and numerical methods. The physical model is a large machine with a height of 34 m and a width of 77 m, and due to its complexity, a simplified model was used. This study aims to investigate the influence of wind speed on the stability failure of the reclaimer and to provide a more efficient and precise stopping criterion. The simulations were performed using a two-way FSI (fluid–structure interaction) approach. An FSI analysis was performed to study the dynamic behavior of a numerical model consisting of two separate parts with contact constraints. This article also highlights the importance of FSI in improving the reliability of the stability failure. Finally, the numerical results showed differences compared to the analytical model, and the wind load limit to stability failure was observed at higher wind speeds. The structure was able to support wind velocities higher than suggested by the FEM (European Materials Handling Federation) standard without stability fails.
The Effect of Heat- and Salt Treatment on the Stability and Rheological Properties of Chickpea Protein-Stabilized Emulsions
Authors: Mańko-Jurkowska Diana , Domian Ewa
Published: March 2024

The aim of the study was to evaluate the effect of heat- (95 °C) and/or salt (0.1 M NaCl) treatment on the physical stability and rheological properties of oil-in-water emulsions stabilized with chickpea protein concentrates (CPCs) for various purposes. Thus, the particle size distribution (PSD), shear behavior, and long-term Turbiscan stability of the prepared emulsions were examined. The oscillatory (dynamic) measurements were also performed to obtain information on the viscoelasticity of tested fluids during thermal treatment. The obtained results indicated that the emulsion stabilized with gelling CPC (eCg) was Newtonian fluid with a homogeneous structure, but susceptible to creaming. Heat-treated eCg exhibited a sol–gel transition at 86 °C and formed fine-stranded aggregates without affecting stability. In turn, heat-induced gelation of eCg in the presence of 0.1 M NaCl resulted in the formation of an aggregated, spatial gel network, stabilization of the system, and a significant change in both shear rheological properties and PSD. Contrariwise, emulsions stabilized with standard CPC (eCs) were unstable heterogeneous systems containing both fine particles < 1 μm and coarse particles of about 100 μm, exhibiting shear-thinning and yield stress. The heat-induced viscoelasticity of eCs was reversible, while heat- and salt-treated emulsions did not form a gel.
Investigating the Relationship between Noise Exposure and Human Cognitive Performance: Attention, Stress, and Mental Workload Based on EEG Signals Using Power Spectrum Density
Authors: Astuti Rahmaniyah Dwi , Suhardi Bambang , Laksono Pringgo Widyo , Susanto Novie
Published: March 2024

A pervasive environmental stressor is one that damages mental and physical health as well as cognitive abilities by producing noise at a specific frequency and level. Current noise pollution levels pose a significant threat to public health, potentially leading to impaired cognitive function, increased stress, and other negative health consequences. This study aims to investigate the relationship between noise exposure and human cognitive abilities using a comprehensive analysis of power spectrum density (PSD) derived from EEG signals. Twenty-four participants completed the experiment to identify the effect of exposure to different noise levels (55 dB, 65 dB, 70 dB, 75 dB, 80 dB, and 85 dB) and two types of continuous and intermittent noise. The Stroop Color–Word Test and the Emotive Epoch EEG are cognitive task instruments used during experiments. Behavioral performance (accuracy and response time) and power spectrum electroencephalographic density were collected and analyzed. The methodology involved collecting EEG data from participants exposed to controlled noise stimuli and a subsequent PSD analysis to uncover frequency-specific patterns associated with cognitive processes. Attention levels were measured by examining beta wave activity, while stress responses were evaluated through an alpha wave analysis. Additionally, mental workload was assessed by considering the overall distribution of PSD through the theta-to-alpha ratio. The results revealed a significant relationship between the exposure to noise types and levels and human cognitive ability. The analysis of the power spectrum density on the cognitive aspects of attention and stress yielded results indicating that participants were in the best attention condition and in a relaxed or unstressed state when exposed to noise levels of 65 dB in both continuous and intermittent noise types. For the mental workload aspect, participants exposed to both continuous and intermittent noise types at a noise level of 70 dB began to indicate the presence of mental workload. These findings supported the importance of considering the impact of environmental noise on human cognitive well-being and demonstrated the potential of EEG monitoring as an objective tool for assessing the impact of noise on cognitive performance.
Continuous Eddy Simulation (CES) of Transonic Shock-Induced Flow Separation
Authors: Fagbade Adeyemi , Heinz Stefan
Published: March 2024

Reynolds-averaged Navier–Stokes (RANS), large eddy simulation (LES), and hybrid RANS-LES, first of all wall-modeled LES (WMLES) and detached eddy simulation (DES) methods, are regularly applied for wall-bounded turbulent flow simulations. Their characteristic advantages and disadvantages are well known: significant challenges arise from simulation performance, computational cost, and functionality issues. This paper describes the application of a new simulation approach: continuous eddy simulation (CES). CES is based on exact mathematics, and it is a minimal error method. Its functionality is different from currently applied simulation concepts. Knowledge of the actual amount of flow resolution enables the model to properly adjust to simulations by increasing or decreasing its contribution. The flow considered is a high Reynolds number complex flow, the Bachalo–Johnson axisymmetric transonic bump flow, which is often applied to evaluate the performance of turbulence models. A thorough analysis of simulation performance, computational cost, and functionality features of the CES model applied is presented in comparison with corresponding features of RANS, DES, WMLES, and wall-resolved LES (WRLES). We conclude that CES performs better than RANS, DES, WMLES, and even WRLES at a little fraction of computational cost applied for the latter methods. CES is independent of usual functionality requirements of other methods, which offers relevant additional advantages.
Research on the Processing of Image and Spectral Information in an Infrared Polarization Snapshot Spectral Imaging System
Authors: Shen Bo , Lv Jinguang , Liang Jingqiu , Zhao Baixuan , Chen Yupeng , Zheng Kaifeng , Zhao Yingze , Qin Yuxin , Wang Weibiao , Liu Guohao
Published: March 2024

In order to solve the problems of a low target recognition rate and poor real-time performance brought about by conventional infrared imaging spectral detection technology under complex background conditions or in the detection of targets of weak radiation or long distance, a kind of infrared polarization snapshot spectral imaging system (PSIFTIS) and a spectrum information processing method based on micro-optical devices are proposed in this paper, where the synchronous acquisition of polarization spectrum information is realized through the spatial modulation of phase with a rooftop-shaped multi-stage micro-mirror and the modulation of the polarization state of light with a micro-nanowire array. For the polarization interference image information obtained, the infrared polarization spectrum decoupling is realized by image segmentation, optical path difference matching, and image registration methods, the infrared polarization spectrum reconstruction is realized by Fourier transform spectral demodulation, and the infrared polarization image fusion is realized by decomposing and reconstructing the high- and low-frequency components of the polarization image based on the Haar wavelet transform. The maximum spectral peak wavenumber error of the four polarization channels of the polarization spectrum reconstruction is less than 2 cm−1, and the polarization angle error is within 1°. Ultimately, compared with the unprocessed polarization image unit, the peak signal-to-noise ratio is improved by 45.67%, the average gradient is improved by 8.03%, and the information entropy is improved by 56.98%.
Investigating the Out-of-Plane Bending Stiffness Properties in Hybrid Species Diagonal-Cross-Laminated Timber Panels
Authors: Kurzinski Shaghayegh , Crovella Paul L.
Published: March 2024

Since the introduction of Cross-laminated Timber (CLT) in Austria in the early 1990s, the adoption of this 90°-crosswise-laminated product has seen exponential growth worldwide. Compared to traditional laminated timber products (e.g., glulam), CLT provides improved dimensional stability but with reduced out-of-plane bending stiffness. To improve the bending stiffness, while maintaining relative dimensional stability, a modified orientation of the inner layers in a diagonal direction can be used. This novel product is Diagonal-Cross-laminated Timber (DCLT), a composite timber product, consisting of inner layers which are rotated at different angle-ply orientations between 0 and 90 degrees to the outer layers. To properly model the out-of-plane bending behavior of the DCLT, analytical models and finite element analysis (FEA) were used, and the results were validated by four-point bending tests performed on DCLT panels with angle-ply orientations of 10°, 20°, 40°, 70°, and a conventional CLT 90° panel. The results indicate that DCLT panels with angle-ply cross layers have a structural advantage in out-of-plane bending over traditional CLT (90°) panels. The apparent bending stiffness from DCLT 90° to DCLT ± 10° has an increase of 33%, 24%, and 35%, respectively, regarding the assessed methods of experimental, theoretical, and FEM modeling. Using these panels would allow for increased spans or load-carrying capacity for a given panel span-to-depth ratio. The development of DCLT and its introduction to the industry not only could enable the use of lower-quality timber that would not otherwise satisfy structural requirements for CLT but also could help reduce the fabrication cost of CLT due to utilizing lower amounts of fiber.
SatelliteRF: Accelerating 3D Reconstruction in Multi-View Satellite Images with Efficient Neural Radiance Fields
Authors: Zhou Xin , Wang Yang , Lin Daoyu , Cao Zehao , Li Biqing , Liu Junyi
Published: March 2024

In the field of multi-view satellite photogrammetry, the neural radiance field (NeRF) method has received widespread attention due to its ability to provide continuous scene representation and realistic rendering effects. However, the satellite radiance field methods based on the NeRF are limited by the slow training speed of the original NeRF, and the scene reconstruction efficiency is low. Training for a single scene usually takes 8–10 h or even longer, which severely constrains the utilization and exploration of the NeRF approach within the domain of satellite photogrammetry. In response to the above problems, we propose an efficient neural radiance field method called SatelliteRF, which aims to quickly and efficiently reconstruct the earth’s surface through multi-view satellite images. By introducing innovative multi-resolution hash coding, SatelliteRF enables the model to greatly increase the training speed while maintaining high reconstruction quality. This approach allows for smaller multi-layer perceptron (MLP) networks, reduces the computational cost of neural rendering, and accelerates the training process. Furthermore, to overcome the challenges of illumination changes and transient objects encountered when processing multi-date satellite images, we adopt an improved irradiance model and learn transient embeddings for each image. This not only increases the adaptability of the model to illumination variations but also improves its ability to handle changing objects. We also introduce a loss function based on stochastic structural similarity (SSIM) to provide structural information of the scene for model training, which further improves the quality and detailed performance of the reconstructed scene. Through extensive experiments on the DFC 2019 dataset, we demonstrate that SatelliteRF is not only able to significantly reduce the training time for the same region from the original 8–10 h to only 5–10 min but also achieves better performance in terms of rendering and the reconstruction quality.
Nutritional Composition and Safety Parameters of Mealworms (Tenebrio molitor) Reared on Substrates Derived from By-Products
Authors: Jankauskienė Agnė , Aleknavičius Dominykas , Andrulevičiūtė Vaida , Mockus Ernestas , Bartkienė Elena , Juknienė Ignė , Kiseliovienė Sandra , Zavistanavičiūtė Paulina , Zaborskienė Gintarė , Kabašinskienė Aistė
Published: March 2024

Mealworms provide a viable option for transforming agricultural and food processing by-products that can be converted into a valuable source of high-quality protein and fat suitable for both animals and humans. Hence, our investigation was aimed at employing sprouted and green potatoes, wheat bran, and by-products from brewers’ production as a comprehensive substrate for rearing mealworms. The nutritional value (fat and protein content) and composition of amino acids (AAs) and fatty acids (FAs) were tested in lyophilized and milled larvae. The results showed that the highest amount of protein was detected in sample 3L (59.18 ± 007%), grown on brewers’ spent grain, whereas sample 2S (with wheat bran) comes out with the highest fat content (34.22 ± 0.491%). It was found that the amount of FAs in the larvae depended on the substrate used: the statistically highest amount of monounsaturated FAs was detected in the sample with sprouted potatoes (1L), the highest content of omega-3 FAs was found in the control sample (4CL), with agar–agar gels, and the sample with brewers spent grains (3L) showed a statistically higher amount of oleic acid. Meanwhile, the highest content of total polyunsaturated FAs (36.23%) was detected in the sample with wheat bran (2L). During the study, 16 distinct AAs have been analyzed, and sample 3L has demonstrated the highest content in 11 instances. It is noteworthy that the sample containing brewers’ spent grain exhibited the highest peroxide levels, indicating oxidation. Meanwhile, the determined number of volatile fatty acids did not exceed the regulatory limits for meat. In summary, it can be asserted that adjusting the substrate is essential for extracting specific amino acids and FAs. However, this could potentially affect the content of peroxides. This adaptation enables the desired chemical composition in larvae, making it suitable for specific purposes such as animal or human nutrition and health enhancement.
Virtual Reality and Internet of Things Based Digital Twin for Smart City Cross-Domain Interoperability
Authors: del Campo Guillermo , Saavedra Edgar , Piovano Luca , Luque Francisco , Santamaria Asuncion
Published: March 2024

The fusion of Internet of Things (IoT), Digital Twins, and Virtual Reality (VR) technologies marks a pivotal advancement in urban development, offering new services to citizens and municipalities in urban environments. This integration promises enhanced urban planning, management, and engagement by providing a comprehensive, real-time digital reflection of the city, enriched with immersive experiences and interactive capabilities. It enables smarter decision-making, efficient resource management, and personalized citizen services, transforming the urban landscape into a more sustainable, livable, and responsive environment. The research presented herein focuses on the practical implementation of a DT concept for managing cross-domain smart city services, leveraging VR technology to create a virtual replica of the urban environment and IoT devices. Imperative for cross-domain city services is interoperability, which is crucial not only for the seamless operation of these advanced tools but also for unlocking the potential of cross-service applications. Through the deployment of our model at the IoTMADLab facilities, we showcase the integration of IoT devices within varied urban infrastructures. The outcomes demonstrate the efficacy of VR interfaces in simplifying complex interactions, offering pivotal insights into device functionality, and enabling informed decision-making processes.
Learning-Based Proof of the State-of-the-Art Geometric Hypothesis on Depth-of-Field Scaling and Shifting Influence on Image Sharpness
Authors: Khatibi Siamak , Wen Wei , Emam Sayyed Mohammad
Published: March 2024

Today, we capture and store images in a way that has never been possible. However, huge numbers of degraded and blurred images are captured unintentionally or by mistake. In this paper, we propose a geometrical hypothesis stating that blurring occurs by shifting or scaling the depth of field (DOF). The validity of the hypothesis is proved by an independent method based on depth estimation from a single image. The image depth is modeled regarding its edges to extract amplitude comparison ratios between the generated blurred images and the sharp/blurred images. Blurred images are generated by a stepwise variation in the standard deviation of the Gaussian filter estimate in the improved model. This process acts as virtual image recording used to mimic the recording of several image instances. A historical documentation database is used to validate the hypothesis and classify sharp images from blurred ones and different blur types. The experimental results show that distinguishing unintentionally blurred images from non-blurred ones by a comparison of their depth of field is applicable.
Dynamic Modeling and Altitude Control for Flying Cars Based on Active Disturbance Rejection Control
Authors: Xu Jie , Lu Xinjiang , Luo Wei , Sun Hao , Long Zhenkun , Xu Yuteng
Published: March 2024

Flying cars offer huge advantages due to their deformable structure, which can adapt to external environments and mission requirements. They represent a novel system that can realize vertical takeoff and landing. However, the structure of a flying car is complicated, placing higher requirements on modeling accuracy and control effectiveness. Thus, in this paper, a dynamic model of a flying car is proposed by combining a car body, motor, and propellers. Then, a double-loop controller based on active disturbance rejection control is proposed to accurately control its flight altitude. Utilizing the extended state observer, external wind and other disturbances are regarded as an extended state, which can be dynamically observed and compensated to significantly improve tracking accuracy. The effectiveness of the proposed controller is validated through detailed simulations and flight experiments. The proposed controller significantly improves control accuracy and disturbance rejection capability.
The Influence of Technological Shifts in the Food Chain on the Emergence of Foodborne Pathogens: An Overview
Authors: Hamaideh Saja , Olaimat Amin , Al-Holy Murad , Ababneh Ahmad , Shahbaz Hafiz , Abughoush Mahmoud , Al-Nabulsi Anas , Osaili Tareq , Ayyash Mutamed , Holley Richard
Published: March 2024

The transformation of the food chain due to technological advances has had significant implications in regard to food safety. A noteworthy trend in this evolution relates to the emergence of new or previously unseen pathogens within products, thereby altering the landscape of foodborne illness epidemiology. The escalating frequency of these events underscores the need for a comprehensive re-evaluation of preventive strategies. The occurrence of novel species of bacteria, viruses, parasites, and unusual biotoxins from unexpected sources has challenged the previous limits that had been set to prevent foodborne illness outbreaks. The repercussions, ranging from detrimental effects on public health to economic burden, are influenced by a myriad of factors affecting the evolution of foodborne pathogens and emerging ailments. Among these factors are shifts in population demographics and behaviors, especially dietary patterns, as well as climate extremes, advances in more precise pathogen detection, microbial adaptation, evolving agricultural practices, and transformative changes within the food industry. This review critically examines the impact of technological metamorphosis along the food chain, encompassing production, processing, handling, packaging, storage, transportation, and industry demographics on the dynamics influencing the emergence of foodborne pathogens. Additionally, potential solutions to mitigate and manage this escalating issue are proposed.
Research on Prediction Model of Particulate Matter in Dalian Street Canyon
Authors: Song Xiaocheng , He Yuehui , Zhang Yao , Zhang Guoxin , Zhou Kai , Que Jinhua
Published: March 2024

In urban areas where populations commonly reside, particle mass concentrations in street canyons can pose significant risks to human health. This study aimed to investigate the diffusion mechanism of particle mass concentrations in urban street canyons by developing and applying a prediction model based on the mathematical modeling of physical processes. The prediction model considered factors such as the influence of traffic wind, natural wind, traffic flow, and other relevant variables influencing particle mass concentrations in street canyons. Field measurements were conducted in Dalian, China, to verify the feasibility of the model. Particle mass concentrations, traffic flow, temperature, relative humidity, and wind speed were measured on Shichang Street (a two-lane one-way road), Tangshan Street (a four-lane two-way road), and Shengli Road (a six-lane two-way road). The results indicated that the majority of traffic peaks occurred around 19:00 on all road types. The PM1.0 mass concentration was well diluted on the four-lane two-way road, with the least dilution observed on the two-lane one-way road. A strong correlation between the particle mass concentrations and traffic flow was discovered. Furthermore, a prediction model was established, accurately predicting the particle mass concentrations when the prediction step was from 5 to 15 s. The coefficient of determination (R2) between the predicted and measured values on the two-lane one-way road, four-lane two-way road, and six-lane two-way road was 0.9319, 0.6582, and 0.9238, respectively. Additionally, the prediction model allowed for a detailed analysis of traffic flow limitations, corresponding to the recommended World Health Organization (WHO) PM2.5 values. Overall, the findings of this study offer valuable insights for forecasting particle exposure levels in street canyons.
Is Recent Warming Exceeding the Range of the Past 125,000 Years?
Authors: Esper Jan , Schulz Philipp , Büntgen Ulf
Published: March 2024

The Intergovernmental Panel on Climate Change (IPCC) concluded that the latest decade was warmer than any multi-century period over the past 125,000 years. This statement rests on a comparison of modern instrumental measurements against the course of past temperatures reconstructed from natural proxy archives, such as lake and marine sediments, and peat bogs. Here, we evaluate this comparison with a focus on the hundreds of proxy records developed by paleoclimatologists across the globe to reconstruct climate variability over the Holocene (12,000 years) and preceded by the Last Glacial Period (125,000 years). Although the existing proxy data provide a unique opportunity to reconstruct low-frequency climate variability on centennial timescales, they lack temporal resolution and dating precision for contextualizing the most recent temperature extremes. While the IPCC’s conclusion on the uniqueness of latest-decade warming is thus not supported by comparison with these smoothed paleotemperatures, it is still likely correct as ice core-derived forcing timeseries show that greenhouse gases were not elevated during any pre-instrumental period of the Holocene.
Fractional Order Mathematical Modelling of HFMD Transmission via Caputo Derivative
Authors: Mohandoss Aakash , Chandrasekar Gunasundari , Meetei Mutum Zico , Msmali Ahmed H.
Published: March 2024

This paper studies a nonlinear fractional mathematical model for hand, foot, and mouth Disease (HFMD), incorporating a vaccinated compartment. Our initial focus involves establishing the non-negativity and boundedness of the fractional order dynamical model. The existence and uniqueness of the system are discussed using the Caputo derivative operator formulation. Applying a fixed-point approach, we obtain results that confirm the presence of at least one solution. We analyze the stability behavior at the two equilibrium points (disease-free and endemic states) of the model and derive the basic reproduction number. Numerical simulations are conducted using the fractional Euler approach, and the simulation results confirm our analytical conclusions. This comprehensive approach enhances the understanding of HFMD dynamics and facilitates the policy making of health care centers to control the further spread of this disease.
Pricing Chinese Convertible Bonds with Learning-Based Monte Carlo Simulation Model
Authors: Zhu Jiangshan , Wen Conghua , Li Rong
Published: March 2024

In this paper, we explore a novel model for pricing Chinese convertible bonds that seamlessly integrates machine learning techniques with traditional models. The least squares Monte Carlo (LSM) method is effective in handling multiple state variables and complex path dependencies through simple regression analysis. In our approach, we incorporate machine learning techniques, specifically support vector regression (SVR) and random forest (RF). By employing Bayesian optimization to fine-tune the random forest, we achieve improved predictive performance. This integration is designed to enhance the precision and predictive capabilities of convertible bond pricing. Through the use of simulated data and real data from the Chinese convertible bond market, the results demonstrate the superiority of our proposed model over the classic LSM, confirming its effectiveness. The development of a pricing model incorporating machine learning techniques proves particularly effective in addressing the complex pricing system of Chinese convertible bonds. Our study contributes to the body of knowledge on convertible bond pricing and further deepens the application of machine learning in the field in an integrated and supportive manner.
Ovotestis Isolation and Cryopreservation of Nesiohelix samarangae (Oriental Snail) as a Snail Model for Conserving Other Endangered Snail Species
Authors: Jeong Jukyeong , Lee Seungki , Choi Jung Kyu
Published: March 2024

This study aimed to develop a cryopreservation system for the reproductive organs of Nesiohelix samarangae (oriental snail) to support the conservation of their species. The reproductive glands of N. samarangae are divided into numerous acini by acinar boundaries. Within each acinus, the presence of spermatogonia, spermatocytes, spermatids, and sperm were observed, indicating various stages of sperm development. The spermatocytes were irregular in shape and possessed large nuclei. Spermatids, on the other hand, were predominantly located within the lumen of the tissue and exhibited densely packed nuclei. Furthermore, sperm with tails attached were observed within the tissue. In order to preserve the oriental snail species, we utilized the vitrification method to freeze the reproductive organs. Comparing the two methods, it was observed that cryopreservation of ovotestis using 2% alginate encapsulation exhibited superior viability following thawing, surpassing the viability achieved with the non-encapsulated approach. In this study, the establishment of a cryopreservation system for the reproductive organs of the oriental snail not only contributes to the genetic conservation of the endangered snail species but also plays a role in maintaining genetic resources and diversity.
Inflammation and Organic Cation Transporters Novel (OCTNs)
Authors: Pochini Lorena , Galluccio Michele , Console Lara , Scalise Mariafrancesca , Eberini Ivano , Indiveri Cesare
Published: March 2024

Inflammation is a physiological condition characterized by a complex interplay between different cells handled by metabolites and specific inflammatory-related molecules. In some pathological situations, inflammation persists underlying and worsening the pathological state. Over the years, two membrane transporters namely OCTN1 (SLC22A4) and OCTN2 (SLC22A5) have been shown to play specific roles in inflammation. These transporters form the OCTN subfamily within the larger SLC22 family. The link between these proteins and inflammation has been proposed based on their link to some chronic inflammatory diseases such as asthma, Crohn’s disease (CD), and rheumatoid arthritis (RA). Moreover, the two transporters show the ability to mediate the transport of several compounds including carnitine, carnitine derivatives, acetylcholine, ergothioneine, and gut microbiota by-products, which have been specifically associated with inflammation for their anti- or proinflammatory action. Therefore, the absorption and distribution of these molecules rely on the presence of OCTN1 and OCTN2, whose expression is modulated by inflammatory cytokines and transcription factors typically activated by inflammation. In the present review, we wish to provide a state of the art on OCTN1 and OCTN2 transport function and regulation in relationships with inflammation and inflammatory diseases focusing on the metabolic signature collected in different body districts and gene polymorphisms related to inflammatory diseases.
Is Chronic Kidney Disease Due to Cadmium Exposure Inevitable and Can It Be Reversed?
Authors: Satarug Soisungwan
Published: March 2024

Cadmium (Cd) is a metal with no nutritional value or physiological role. However, it is found in the body of most people because it is a contaminant of nearly all food types and is readily absorbed. The body burden of Cd is determined principally by its intestinal absorption rate as there is no mechanism for its elimination. Most acquired Cd accumulates within the kidney tubular cells, where its levels increase through to the age of 50 years but decline thereafter due to its release into the urine as the injured tubular cells die. This is associated with progressive kidney disease, which is signified by a sustained decline in the estimated glomerular filtration rate (eGFR) and albuminuria. Generally, reductions in eGFR after Cd exposure are irreversible, and are likely to decline further towards kidney failure if exposure persists. There is no evidence that the elimination of current environmental exposure can reverse these effects and no theoretical reason to believe that such a reversal is possible. This review aims to provide an update on urinary and blood Cd levels that were found to be associated with GFR loss and albuminuria in the general populations. A special emphasis is placed on the mechanisms underlying albumin excretion in Cd-exposed persons, and for an accurate measure of the doses–response relationships between Cd exposure and eGFR, its excretion rate must be normalised to creatinine clearance. The difficult challenge of establishing realistic Cd exposure guidelines such that human health is protected, is discussed.
Real-Time Monitoring of a Nucleic Acid Amplification Reaction Using a Mass Sensor Based on a Quartz-Crystal Microbalance
Authors: Kumagai Hideto , Furusawa Hiroyuki
Published: March 2024

Nucleic acid amplification reactions such as polymerase chain reaction (PCR), which uses a DNA polymerase to amplify individual double-stranded DNA fragments, are a useful technique for visualizing the presence of specific genomes. Although the fluorescent labeling method is mainly used with DNA amplification, other detection methods should be considered for further improvements, such as miniaturization and cost reduction, of reaction-monitoring devices. In this study, the quartz-crystal microbalance (QCM) method, which can measure nanogram-order masses, was applied for the real-time detection of DNA fragments in a solution with nucleic acids. This was combined with an isothermal nucleic acid amplification reaction based on the recombinase polymerase amplification (RPA) method, which allowed DNA amplification at a constant temperature. When the DNA amplification reaction was initiated on a QCM sensor plate with an immobilized primer DNA strand, a significant increase in mass was observed compared to when the primer DNA was not immobilized. QCM was shown to be sufficiently sensitive for the in situ detection of amplified DNA fragments. Combining a portable QCM device and RPA offers a sensitive point-of-care method for detecting nucleic acids.
Machine Learning-Assisted Classification of Paraffin-Embedded Brain Tumors with Raman Spectroscopy
Authors: Klamminger Gilbert Georg , Mombaerts Laurent , Kemp Françoise , Jelke Finn , Klein Karoline , Slimani Rédouane , Mirizzi Giulia , Husch Andreas , Hertel Frank , Mittelbronn Michel , Kleine Borgmann Felix B.
Published: March 2024

Raman spectroscopy (RS) has demonstrated its utility in neurooncological diagnostics, spanning from intraoperative tumor detection to the analysis of tissue samples peri- and postoperatively. In this study, we employed Raman spectroscopy (RS) to monitor alterations in the molecular vibrational characteristics of a broad range of formalin-fixed, paraffin-embedded (FFPE) intracranial neoplasms (including primary brain tumors and meningiomas, as well as brain metastases) and considered specific challenges when employing RS on FFPE tissue during the routine neuropathological workflow. We spectroscopically measured 82 intracranial neoplasms on CaF2 slides (in total, 679 individual measurements) and set up a machine learning framework to classify spectral characteristics by splitting our data into training cohorts and external validation cohorts. The effectiveness of our machine learning algorithms was assessed by using common performance metrics such as AUROC and AUPR values. With our trained random forest algorithms, we distinguished among various types of gliomas and identified the primary origin in cases of brain metastases. Moreover, we spectroscopically diagnosed tumor types by using biopsy fragments of pure necrotic tissue, a task unattainable through conventional light microscopy. In order to address misclassifications and enhance the assessment of our models, we sought out significant Raman bands suitable for tumor identification. Through the validation phase, we affirmed a considerable complexity within the spectroscopic data, potentially arising not only from the biological tissue subjected to a rigorous chemical procedure but also from residual components of the fixation and paraffin-embedding process. The present study demonstrates not only the potential applications but also the constraints of RS as a diagnostic tool in neuropathology, considering the challenges associated with conducting vibrational spectroscopic analysis on formalin-fixed, paraffin-embedded (FFPE) tissue.
Narrative-Derived Indices of Metacognition among People with Schizophrenia: Associations with Self-Reported and Performance-Based Social Functioning
Authors: Kilicoglu Melissa F. V. , Lundin Nancy B. , Angers Kaley , Moe Aubrey M.
Published: March 2024

Metacognitive functioning—which broadly encompasses the mental processes involved in thinking about the thinking of one’s self and the thinking of others—is often impaired among individuals living with schizophrenia and may contribute to difficulties in social and interpersonal functioning. Although the majority of studies assessing metacognition among individuals with schizophrenia use standardized, laboratory-based measurements, an increasing number of studies have measured metacognitive capacity using natural language produced by individuals living with mental illness. At the same time, less is known about how language-derived indices of metacognitive function relate to key social outcomes among people with schizophrenia. The primary objective of this study was to employ a validated language coding system (the Metacognition Assessment Scale, Abbreviated; MAS-A) to assess metacognitive functioning from the spoken life narratives of individuals with schizophrenia (n = 32) and community controls (n = 15). Among individuals with schizophrenia, we also examined the associations between language-derived metacognition and measures of self-reported and performance-based social functioning. Our results suggest that most aspects of metacognition in our sample were not significantly diminished in people with schizophrenia compared to community controls. Unexpectedly, the MAS-A subscale related to one’s ability to master psychological difficulties was rated higher among individuals with schizophrenia. Further, our results suggest that among people with schizophrenia, higher metacognitive functioning in the domain of self-reflectivity was associated with poorer self-reported social functioning, while a greater metacognitive awareness of other individuals’ minds was associated with better scores on aspects of performance-based social functioning. Collectively, these results underscore the utility of assessing metacognitive functioning via life-story narratives to understand social outcomes and highlight possible aspects of resiliency among individuals who have experienced a serious mental illness.
Effects of Yachting Motivation on Yachting Satisfaction and Re-Yachting Intention
Authors: Ha Jaehyun , Cho Dongwook
Published: March 2024

It is clear that yachting tourists are motivated to spend their leisure time at sea. However, few studies have determined the relationship between tourists’ motivation and satisfaction with yachting, and re-yachting intention. Furthermore, the purpose of this study was to examine the relationships among yachting motivation, yachting satisfaction, and re-yachting intention. More specifically, this study sought to examine whether yachting motivation influenced yachting satisfaction, and determine if re-yachting intention was affected by yachting motivation. In order to analyze the data for this study, a total of 240 questionnaires were distributed to yachting tourists at three private yacht club operators, utilizing the convenient sampling method. A total of 219 usable questionnaires were analyzed for this study, while 21 questionnaires were discarded due to incompletion of the survey. Data were analyzed with multiple regression analysis using SPSS version 27.0. The results revealed that entertainment, stress reduction, and family/friends were positively and significantly related to yachting satisfaction. However, socializing and external ostentation did not contribute to yachting satisfaction. Secondly, the results indicated that entertainment, socializing, and stress reduction had a positive and significant effect on re-yachting intention. Conversely, external ostentation and family/friends had no significant influence on re-yachting intention. It is necessary for yacht club business operators to recognize the yachting motivation of the participants. It is also recommended that appropriate marketing strategies are implemented to increase yachting tourism, which would possibly influence yachting satisfaction and re-yachting intention.
Optimal Microgrids in Buildings with Critical Loads and Hybrid Energy Storage
Authors: Rosales-Asensio Enrique , de Loma-Osorio Iker , Palmero-Marrero Ana I. , Pulido-Alonso Antonio , Borge-Diez David
Published: March 2024

This research aims to optimize and compare the annual costs of energy services in buildings with critical loads and analyze case studies for hospitals and higher education institutions in the United States. Besides electricity and natural gas costs, the study considers all the infrastructure costs of capital amortization and maintenance. In addition, it studies energy resilience improvement due to distributed generation, including solar photovoltaic, solar thermal, internal combustion engine, and fuel cell sources. The optimization considers the electrical consumption, the heating and cooling demands, and the operational strategy of the energy storage systems. To simulate real scenarios, energy tariffs were modeled and considered, and final optimization results were produced. Some of the microgrid load was considered critical to model resilience benefits. The results show that if favorable energy tariffs are applied, the benefits of increasing energy resilience represent a novel market with high potential in facilities with significant critical loads. This methodology can be used in similar scenarios, adapting each particular load profile and critical load to provide a combined optimal solution regarding resilience and economic benefits.
Experimental Study on Strength and Microstructure of Loess Improved by CG-2 Curing Agent and Cement
Authors: Ma Xuening , Liu Yuhang , Yin Wenhua , Wang Xiaodong , Guo Shulin
Published: March 2024

In order to study the improvement effect of the CG-2 curing agent and cement on loess, a series of physical and mechanical property tests and microstructure tests were carried out on loess improved with different dosages of curing agent and cement to study the physical and mechanical properties, durability and microscopic pore characteristics of the CG-2 curing agent and cement-improved loess. The results show that the unconfined compressive strength of improved loess increases gradually with the increase in curing agent and cement dosage, and the higher the compaction degree and the longer the curing age, the higher the unconfined compressive strength. In the case of the same cement content, the higher the dosage of curing agent, the more the unconfined compressive strength of improved loess increases. Under the condition of reaching the same unconfined compressive strength, the addition of curing agent can significantly reduce the amount of cement. The more the content of cement and curing agent, the less the unconfined compressive strength decreases after a certain number of freeze–thaw cycles, and the higher the dry-wet cycles index after a certain number of dry-wet cycles, indicating that the addition of curing agent can significantly improve the ability of the sample to resist freeze–thaw cycles and dry–wet cycles. According to the microscopic test results, it is found that the addition of curing agent can reduce the porosity of soil particles, change the contact and arrangement mode between soil particles, and enhance the agglomeration and cementation characteristics between soil particles, and obviously improve the physical and mechanical properties of soil. The research results can provide new ideas and methods for the improvement technology of loess.
Urodynamic Parameters and Continence Outcomes in Asymptomatic Patients with Ileal Orthotopic Neobladder: A Systematic Review and Metanalysis
Authors: Asimakopoulos Anastasios D. , Finazzi Agrò Enrico , Piechaud Thierry , Gakis Georgios , Gaston Richard , Rosato Eleonora
Published: March 2024

Introduction: The orthotopic neobladder is the type of urinary diversion (UD) that most closely resembles the original bladder. However, in the literature the urodynamic aspects are scarcely analysed. Objective: To provide the first systematic review (SR) on the urodynamic (UDS) outcomes of the ileal orthotopic neobladders (ONB). Continence outcomes are also presented. Methods: A PubMed, Embase and Cochrane CENTRAL search for peer-reviewed studies on ONB published between January 2001–December 2022 was performed according to the Preferred Reporting Items for Systematic Review and Meta-analysis (PRISMA) statement. Results and Conclusion: Fifty-nine manuscripts were eligible for inclusion in this SR. A great heterogeneity of data was encountered. Concerning UDS parameters, the pooled mean was 406.2 mL (95% CI: 378.9–433.4 mL) for maximal (entero)cystometric capacity (MCC) and 21.4 cmH2O (95% CI: 17.5–25.4 cmH2O) for Pressure ONB at MCC. Postvoid-residual ranged between 4.9 and 101.6 mL. The 12-mo rates of day and night-time continence were 84.2% (95% CI: 78.7–89.1%) and 61.7% (95% CI: 51.9–71.1%), respectively.Despite data heterogeneity, the ileal ONB seems to guarantee UDS parameters that resemble those of the native bladder. Although acceptable rates of daytime continence are reported the issue of high rates of night-time incontinence remains unsolved. Adequately designed prospective trials adopting standardised postoperative care, terminology and methods of outcome evaluation as well as of conduction of the UDS in the setting of ONB are necessary to obtain homogeneous follow-up data and to establish UDS guidelines for this setting.
Racial Differences in Vaginal Fluid Metabolites and Association with Systemic Inflammation Markers among Ovarian Cancer Patients: A Pilot Study
Authors: Osazuwa-Peters Oyomoare L. , Deveaux April , Muehlbauer Michael J. , Ilkayeva Olga , Bain James R. , Keku Temitope , Berchuck Andrew , Huang Bin , Ward Kevin , Gates Kuliszewski Margaret , Akinyemiju Tomi
Published: March 2024

The vaginal microbiome differs by race and contributes to inflammation by directly producing or consuming metabolites or by indirectly inducing host immune response, but its potential contributions to ovarian cancer (OC) disparities remain unclear. In this exploratory cross-sectional study, we examine whether vaginal fluid metabolites differ by race among patients with OC, if they are associated with systemic inflammation, and if such associations differ by race. Study participants were recruited from the Ovarian Cancer Epidemiology, Healthcare Access, and Disparities Study between March 2021 and September 2022. Our study included 36 study participants with ovarian cancer who provided biospecimens; 20 randomly selected White patients and all 16 eligible Black patients, aged 50–70 years. Acylcarnitines (n = 45 species), sphingomyelins (n = 34), and ceramides (n = 21) were assayed on cervicovaginal fluid, while four cytokines (IL-1β, IL-10, TNF-α, and IL-6) were assayed on saliva. Seven metabolites showed >2-fold differences, two showed significant differences using the Wilcoxon rank-sum test (p < 0.05; False Discovery Rate > 0.05), and 30 metabolites had coefficients > ±0.1 in a Penalized Discriminant Analysis that achieved two distinct clusters by race. Arachidonoylcarnitine, the carnitine adduct of arachidonic acid, appeared to be consistently different by race. Thirty-eight vaginal fluid metabolites were significantly correlated with systemic inflammation biomarkers, irrespective of race. These findings suggest that vaginal fluid metabolites may differ by race, are linked with systemic inflammation, and hint at a potential role for mitochondrial dysfunction and sphingolipid metabolism in OC disparities. Larger studies are needed to verify these findings and further establish specific biological mechanisms that may link the vaginal microbiome with OC racial disparities.