bluuebunny/crossref_metadata_2025 huggingface dataset:
Bloodstream Infections in Intensive Care Unit during Four Consecutive SARS-CoV-2 Pandemic Waves
Authors: Pozza Giacomo , Casalini Giacomo , Ciubotariu Cosmin Lucian , Giacomelli Andrea , Galimberti Miriam , Zacheo Martina , Rabbione Andrea , Pieruzzi Margherita , Oreni Letizia , Galimberti Laura , Colombo Riccardo , Rizzardini Giuliano , Pagani Cristina , Rimoldi Sara Giordana , Bonazzetti Cecilia , Ridolfo Anna Lisa , Antinori Spinello
Published: September 2023

Critically ill COVID-19 patients are at an increased risk of bloodstream infections (BSIs). We performed a retrospective observational single-center study on COVID-19 patients admitted to intensive care unit (ICU) to assess the incidence of BSIs in four consecutive periods: 21 February–31 July 2020 (W1), 1 August 2020–31 January 2021 (W2), 1 February–30 September 2021 (W3) and 1 October 2021 and 30 April 2022 (W4). BSIs that occurred 48 h after ICU admission were included. The crude incidence of BSIs was estimated by means of Poisson distribution normalized to 1000 patient-days. A total of 404 critically ill COVID-19 patients were admitted to ICU, of whom 284 (61%) developed at least one episode of BSI with an overall crude incidence of 87 events every 1000 patient-days (95% CI 77–98) without a significant difference in consecutive epidemic periods (p = 0.357). Gram-positive bacteria were the most frequent etiological agents of BSIs, contributing to 74.6% episodes. A progressive decrease in BSIs due to Enterococcus spp. was observed (W1 57.4%, W2 43.7%, W3 35.7% and W4 32.7%; p = 0.004). The incidence of BSIs remained stable during different epidemic periods. Enterococcus spp. prevalence was significantly reduced, although still accounted for one third of BSIs in more recent epidemic periods.
Distributional Representation of Cyclic Alternating Patterns for A-Phase Classification in Sleep EEG
Authors: Vergara-Sánchez Diana Laura , Calvo Hiram , Moreno-Armendáriz Marco A.
Published: September 2023

This article describes a detailed methodology for the A-phase classification of the cyclic alternating patterns (CAPs) present in sleep electroencephalography (EEG). CAPs are a valuable EEG marker of sleep instability and represent an important pattern with which to analyze additional characteristics of sleep processes, and A-phase manifestations have been linked to some specific conditions. CAP phase detection and classification are not commonly carried out routinely due to the time and attention this problem requires (and if present, CAP labels are user-dependent, visually evaluated, and hand-made); thus, an automatic tool to solve the CAP classification problem is presented. The classification experiments were carried out using a distributional representation of the EEG data obtained from the CAP Sleep Database. For this purpose, data symbolization was performed using the one-dimensional symbolic aggregate approximation (1d-SAX), followed by the vectorization of symbolic data with a trained Doc2Vec model and a final classification with ten classic machine learning models for two separate validation strategies. The best results were obtained using a support vector classifier with a radial basis kernel. For hold-out validation, the best F1 Score was 0.7651; for stratified 10-fold cross-validation, the best F1 Score was 0.7611 ± 0.0133. This illustrates that the proposed methodology is suitable for CAP classification.
Multi-Compartment Vehicle Routing Problem Considering Traffic Congestion under the Mixed Carbon Policy
Authors: Fan Xueru , Yao Guanxin , Yang Yang
Published: September 2023

The use of multi-compartment vehicles (MCVs) in urban logistics distribution is increasing. However, urban traffic congestion causes high carbon emissions in the logistics distribution, resulting in unsustainable development in urban transportation. In addition, the application of the mixed carbon policy has gradually become the first choice for energy conservation and emission reduction in some countries and regions. The transportation industry is a major carbon-emitting industry, which needs to be constrained by carbon emission reduction policies. In this context, the research on the multi-compartment vehicle routing problem (MCVRP) considering traffic congestion under the mixed carbon policy is carried out. Firstly, a mathematical model of MCVRP considering traffic congestion under the mixed carbon policy is constructed. Secondly, a two-stage variable neighborhood threshold acceptance algorithm (VNS-TA) is proposed to solve the above mathematical model. Thirdly, 14 adapted standard examples of the MCVRP are used to verify the effectiveness and optimization ability of the two-stage VNS-TA algorithm. A simulation example of the MCVRP considering traffic congestion under the mixed carbon policy is used to conduct sensitivity analyses for different scenarios. Finally, the following conclusions are drawn: (1) the two-stage VNS-TA algorithm is effective and has strong optimization ability in solving the basic MCVRP, and (2) the two-stage VNS-TA algorithm can solve and optimize the MCVRP considering traffic congestion under the mixed carbon policy, which has the effects of cost saving and energy conservation and emission reduction.
Chromatics in Urban Landscapes: Integrating Interactive Genetic Algorithms for Sustainable Color Design in Marine Cities
Authors: Zhang Longlong , Kim Chulsoo
Published: September 2023

Color design plays a pivotal role in determining whether marine urban landscapes meet the diverse needs of individuals, encompassing their visual, psychological, behavioral, and spiritual dimensions. In the contemporary urban environment, a host of practical challenges, including severe color pollution, the absence of regional cultural characteristics, and a lack of humanistic sensitivity in public spaces’ color schemes, necessitates a thorough exploration of the intricate relationship between color and human psychological needs within environmental contexts. This study leverages the potential of interactive genetic algorithms as a powerful tool for innovative color design solutions. Anchored in the nexus of the environment, human psychology, and color theory, this research delves into the intricate nuances of marine urban landscape color. Employing a comprehensive approach that combines questionnaires and extensive field surveys, we seek to elucidate the critical interplay between color and human well-being. Drawing upon the case study of Zhuhai Shijingshan Park, we harness the principles of interactive genetic algorithms to iteratively design marine urban color patterns. Through this experimentation, our study unveils novel design strategies that harmonize with the psychological idiosyncrasies of the human–environment interface. Specifically, the findings of our research highlight the profound impact of color selection on the emotional and behavioral responses of individuals within marine urban landscapes. Our study contributes vital insights into the art and science of marine urban color design, shedding light on the nuanced ways in which color choices can enhance the quality of urban spaces and promote human well-being. This research endeavors to bridge the gap between marine urban design and human psychology through a comprehensive exploration of color design in marine urban landscapes. By addressing the practical challenges and leveraging innovative design techniques, we strive to provide a holistic understanding of the symbiotic relationship between color and human experience, ultimately enriching the design practices that shape our urban environments.
Effect of Simultaneous Changes in Asphalt Binder Bee Structure Components on Mechanical Properties during the Aging and Rejuvenation Process
Authors: Huo Donghui , Yao Xiupeng , Guo Meng , Luo Daisong
Published: September 2023

The bee structure of an asphalt binder surface changes during the aging and rejuvenation process, and the effect of this microstructural change on the mechanical properties of the asphalt binder is not clear. Therefore, in this paper, a two-dimensional finite element model of an asphalt binder microstructure was constructed based on processed AFM images, and the contents of bee phases and bee casings were varied at the same time to analyze the stress and strain distribution law of the asphalt binder microstructure. The results of the study show that in the bee structure, the stress in the bee phase is obviously greater than that in the bee casing, and the stress in the interstitial phase is the lowest. With the simultaneous enhancement in the proportion of the bee phase and the bee casing, the stresses in the asphalt samples increased in all phase structures. Under the combined effect of the decrease in the content of the bee phase and the increase in the content of the bee casing, there is a certain degree of increase in the internal stresses and strains in the asphalt binder, the effect of the bee casing on the internal stresses in the asphalt binder is more pronounced, and the bee phase and the bee casing play better roles in resisting the external deformation due to the increase in the volume fraction. For a recycled asphalt binder, whether there is an increase in the dosage of the old asphalt binder or an enhancement in the interfacial diffusion and a fusion of new and old asphalt binders, the level of tensile strain within the recycled asphalt binder will increase to a certain extent, which, in turn, will put forward a higher requirement for its anti-cracking ability.
An FCM-Based Image De-Noising with Spatial Statistics Pilot Study
Authors: Chen Tzong-Jer
Published: September 2023

Image de-noising is an important scheme that makes an image visually prominent and obtains enough useful information to produce a clear image. Many applications have been developed for effective noise suppression that produce good image quality. This study assumed that a residual image consisted of noise with edges produced by subtracting the original image with a low-pass-filter-smoothed image. The Moran statistics were then used to measure the variation in spatial information in residual images and we then used this information as feature data input into the Fuzzy C-means (FCM) algorithm. Three clusters were pre-assumed for FCM in this work: they were heavy, medium, and less noisy areas. The rates for each position partially belonged to each cluster determined using an FCM membership function. Each pixel in a noisy image was assumed in de-noising processing as a linear combination of the product of three de-noised images with membership functions in the same position. Average filters with different windows and a Gaussian filter were a priori applied to this noisy image to create three de-noised versions. The results showed that this scheme worked better than the non-adaptive smoothing. This scheme‘s performance was evaluated and compared to the bilateral filter and non-local means (NLM) using the peak signal to noise ratio (PSNR) and structure similarity index measure (SSIM). The developed scheme is a pilot study. Further future studies are needed on the optimized number of clusters and smoother versions used in linear combination.
MSREA-Net: An Efficient Skin Disease Segmentation Method Based on Multi-Level Resolution Receptive Field
Authors: Yang Guoliang , Nie Ziling , Wang Jixiang , Yang Hao , Yu Shuaiying
Published: September 2023

Aiming at the low contrast of skin lesion image and inaccurate segmentation of lesion boundary, a skin lesion segmentation method based on multi-level split receptive field and attention is proposed. Firstly, the depth feature extraction module and multi-level splitting receptive field module are used to extract image feature information; secondly, the hybrid pooling module is used to build long-term and short-term dependencies and integrate global information and local information. Finally, the reverse residual external attention module is introduced to construct the decoding part, which can mine the potential relationship between data sets and improve the network segmentation ability. Experiments on ISBI2017 and ISIC2018 data sets show that the Dice similarity coefficient and Jaccard index reach 88.67% and 91.84%, 79.25% and 81.48%, respectively, and the accuracy reaches 93.89% and 96.16%. The segmentation method is superior to the existing algorithms as a whole. Simulation experiments show that the network has a good effect on skin lesion image segmentation and provides a new method for skin disease diagnosis.
Discrimination of Healthy and Cancerous Colon Cells Based on FTIR Spectroscopy and Machine Learning Algorithms
Authors: Lasalvia Maria , Gallo Crescenzio , Capozzi Vito , Perna Giuseppe
Published: September 2023

Colorectal cancer was one of the most frequent causes of death due to cancer in 2020. Current diagnostic methods, based on colonoscopy and histological analysis of biopsy specimens, are partly dependent on the operator’s skills and expertise. In this study, we used Fourier transform infrared (FTIR) spectroscopy and different machine learning algorithms to evaluate the performance of such method as a complementary tool to reliably diagnose colon cancer. We obtained FTIR spectra of FHC and CaCo-2 cell lines originating from healthy and cancerous colon tissue, respectively. The analysis, based on the intensity values of specific spectral structures, suggested differences mainly in the content of lipid and protein components, but it was not reliable enough to be proposed as diagnostic tool. Therefore, we built six machine learning algorithms able to classify the two different cell types: CN2 rule induction, logistic regression, classification tree, support vector machine, k nearest neighbours, and neural network. Such models achieved classification accuracy values ranging from 87% to 100%, sensitivity from 88.1% to 100%, and specificity from 82.9% to 100%. By comparing the experimental data, the neural network resulted to be the model with the best performance parameters, having excellent values of accuracy, sensitivity, and specificity both in the low-wavenumber range (1000–1760 cm−1) and in the high-wavenumber range (2700–3700 cm−1). These results are encouraging for the application of the FTIR technique, assisted by machine learning algorithms, as a complementary diagnostic tool for cancer detection.
Construction of Geosynthetic–Reinforced Pavements and Evaluation of Their Impacts
Authors: Wang Danrong , Wang Sheng-Lin , Tighe Susan , Bhat Sam , Yin Shunde
Published: September 2023

Geosynthetic materials (i.e., geogrids, geotextiles and other geocomposites) act as an interlayer system and are widely used in construction applications. In pavement structures, geosynthetic layers provide potential benefits such as reinforcement, reflective cracking mitigation, increased fatigue life, and improved drainage and filtering. However, few studies have addressed the installation and construction practices of geosynthetics in pavements. Furthermore, the study of geosynthetics and their contribution during construction are limited. In this paper, a full-scale field study was conducted and three trial sections were constructed; two types of geosynthetics, a fibreglass geogrid and a geogrid composite, were installed in the asphalt binder course and at the interface between the subgrade and base layer, respectively, to be compared with a control section without geosynthetic reinforcement. Trial sections were instrumented to monitor the pressure applied on the subgrade, the strain in the base lift of the asphalt binder course, the temperature, and the moisture within the pavement structure during construction. In addition, post-construction field testing was performed to measure the stiffness of the pavements after construction. The results indicated that geosynthetic-reinforced pavements can maintain pavement resilience during construction and significantly mitigate the disturbances caused by construction activities. The geogrid embedded in the asphalt layer was demonstrated to reduce the pressure at the subgrade caused by paving equipment by 70% compared with the control section, while simultaneously reducing the longitudinal and transverse strain at the bottom of the asphalt layer by 54% and 99%. Observations from the geogrid composite test section also demonstrate the potential to minimize the impacts of future freeze–thaw at the subgrade due to the improved drainage and indirect insulation effect.
Surface Quality Evaluation in the Milling Process Using a Ball Nose End Mill
Authors: Varga Ján , Ižol Peter , Vrabeľ Marek , Kaščák Ľuboš , Drbúl Mário , Brindza Jozef
Published: September 2023

Shaped surfaces are increasingly used in the field of mold-making for casting or injection molding, where future products include shapes with different curvatures. These are surfaces that form convex curves, concave curves, or a combination thereof. Given these machined surfaces, it is important to know the impact of the finishing strategies on these surfaces. This paper deals with the comparison of finishing milling strategies in the production of shaped surfaces and the analysis of different methods for the evaluation of surface topography. In addition, the experimental results evaluate the roughness of the machined surface and surface shape variations. The material used for the experiments was AlCu4Mg aluminum alloy, and Constant Z, spiral and spiral circle strategies were chosen for the finishing strategies. The evaluation of surface topography and surface roughness was carried out at three different specimen heights with respect to the tool’s contact with the machined surface.
Influence of Induced Environment Oscillations on Limits of Stability in Healthy Adults
Authors: Wodarski Piotr , Gruszka Grzegorz , Chmura Marta , Ples Marek , Gzik Marek , Jurkojć Jacek
Published: September 2023

(1) Background: Human balance and equilibrium-maintaining abilities have been widely researched up to this day. Numerous publications have investigated the possibilities of enhancing these abilities, bringing the patient back to their original capabilities post-disease or accident, and training for fall prevention. Virtual reality technology (VR) is becoming a progressively more renowned technique for performing or enhancing rehabilitation or training. We aimed to explore whether the introduction of scenery oscillation can influence a person’s limits of stability. (2) Methods: Sixteen healthy adults participated in measurements. Each of them underwent 10 trials, during which subjects were supposed to, on acoustic cue, lean as far forward and back as possible, without raising their heels or toes. Two trials were conducted without the use of VR, four with oscillating scenery, one with stationary scenery, one with displayed darkness, and two trials were performed for reference, which did not require leaning nor used VR technology. (3) Results: For the total as well as for each foot separately, COP displacements and velocities were calculated and analyzed. A post-hoc Wilcoxon pairwise test with Holm’s correction was performed, resulting in 420 returned p-values, 4 of which indicated significant differences between medians when comparing trials with 0.2 Hz oscillating scenery with trials with eyes open and closed. (4) Conclusions: No statistically significant differences at α = 0.05 between reached maximums in trials using VR and trials without it were found, only trials using 0.2 Hz oscillations displayed statistically significant differences when comparing velocities of leaning. The authors believe that such oscillations resemble naturally occurring tinnitus; additionally, low-frequency oscillations are believed to influence postural balance more than high-frequency ones, therefore affecting the velocity and displacements of COP the most.
A Topology-Based Local Identifier Mapping Scheme for Power System Resources in Common Information Model Framework for Interoperability
Authors: Song Jin-Uk , An Jae-Guk , Lim Seong-Il , Oh Yun-Sik
Published: September 2023

The Common Information Model (CIM) defined in international electrotechnical commission technical committee 57 (IEC TC57) has been utilized for achieving interoperability by employing a canonical data model strategy for standardizing interfaces in the power industry. In adopting the CIM framework for data exchange, problems regarding identifiers (IDs) such as two different local IDs for the same object can occur, and local ID mapping tables are required for the object identification in advance of the data exchange. This paper proposes a new local ID mapping scheme using a topological fingerprint (TF) that represents a unique property of a power system resource. The concept of standard information, defined as common data that all systems considered for data exchange have in common, is introduced to make duplicated TFs separable. Case studies considering numerous power system resources in a distribution management system (DMS) are conducted and it can be seen from the simulation results that the proposed scheme can generate a unique TF for every resource in a system by the local ID mappings and automatically create an accurate mapping table of local IDs issued by each system differently.
Detailed Structural Analysis of Cylindrical Steel Tank Subjected to Various Seismic Peak Ground Values Using FSI Approach
Authors: Zulfiqar Yasir , Zulfiqar Asim , Ahmad Hafiz Waqar , Chaudry Umer Masood , Khan Muhammad Kashif , Jun Tea-Sung
Published: September 2023

The seismic analysis of ground-supported cylindrical steel tanks subjected to lateral harmonic displacement loadings has been carried out. This paper numerically evaluates the structural response of various tank geometries due to resonant seismic sloshing. The numerical investigation is performed using a two-way fluid structural interaction approach that couples computational fluid dynamics analysis with finite element transient structural analysis. The results of the analysis have been validated using Seismic Design Code (Eurocode 8, part 4). Regarding tank aspect ratio (H/D), five geometries covering slender, medium, and broad structures are analyzed under ten harmonic base excitations. All the geometries are excited at their first convective frequency, whose shape and magnitude are evaluated using modal analysis. The seismic response curves have been developed for each tank model, which reveal the complex and peculiar structural response. It is observed from the tanks’ seismic response that they undergo three transitional stress zones named safe, yielding, and failure zones. The critical loadings and failure duration have also been evaluated for each tank model. This will help to avoid future structural damage by designing liquid-containing structures based on evaluated seismic failure loads.
Frequency Dependence of the Correlation between Ozone and Temperature Oscillations in the Middle Atmosphere
Authors: Hocke Klemens , Sauvageat Eric
Published: September 2023

This study investigates the frequency dependence of the correlation or anticorrelation of ozone and temperature in the middle atmosphere. The anticorrelation of ozone and temperature plays a role for a possible super recovery of upper stratospheric ozone in the presence of man-made cooling of the middle atmosphere due to increasing carbon dioxide emissions. The correlation between lower stratospheric ozone and temperature indicates the dependence of lower stratospheric temperature trends on the ozone evolution in addition to greenhouse gas emissions. Ozone and temperature measurements of the microwave limb sounder (MLS) on the satellite Aura from 2004 to 2021 are utilized for Bern (46.95° N, 7.44° E) at middle latitudes and for the equator region. The time series are bandpass filtered for periods from 2 days to 5 years. The correlation coefficient depends on the period of the oscillation in temperature and ozone. The strongest correlation and anticorrelation are found for the annual oscillation. The anticorrelation between ozone and temperature in the upper stratosphere is about −0.7 at a period of two days and −0.99 at a period of one year. Thus, the temperature dependence of the ozone reaction rates also leads to an anticorrelation of ozone and temperature at short periods so that ozone can be considered as a tracer of planetary waves. At the equator, a dominant semiannual oscillation and an 11 year solar cycle are found for nighttime ozone in the upper mesosphere. The semiannual oscillation (SAO) in ozone and temperature shows a strong correlation indicating a dynamical control of the ozone SAO in the upper mesosphere. The SAO in the equatorial nighttime values of ozone and temperature is possibly due to a semiannual modulation of vertical advection by the diurnal tide.
Comparison of Portable and Large Mobile Air Cleaners for Use in Classrooms and the Effect of Increasing Filter Loading on Particle Number Concentration Reduction Efficiency
Authors: Duill Finn Felix , Schulz Florian , Jain Aman , van Wachem Berend , Beyrau Frank
Published: September 2023

This study focuses on the effect of portable and large filter-based air cleaners (HEPA filters), which became popular indoors during the COVID-19 pandemic, and their suitability for classrooms (here 186 m3). The decay rates of the particle number concentration (PNC) were measured simultaneously at up to four positions in the room. It was found that the different air outlet configurations of the units have an effect on the actual PNC removal in the room when operated at the same volume flow rates. This effect of the airflow efficiency of the air cleaners (AP) in a classroom is quantified with an introduced Air Cleaning Efficiency Factor in this study to identify beneficial airflows. In this context, the effect of filter loading in long-term operation on the cleaning effect is also investigated. The emitted sound pressure levels of the APs are given special attention as this is a critical factor for use in schools, as well as power consumption. A total of six different devices were tested—two portable APs and four large APs. In order to achieve the necessary volume flow rates, three or four of the portable units were used simultaneously in one room, while only one of the large units was used per room. When used at the same air circulation rates in the room, the portable APs exhibit higher sound pressure levels compared to the large APs. At air circulation rates of 4–5 h−1, the portable APs exceeded a value of 45 dB(A). Two of the four large units reach sound pressure levels below 40 dB(A) at air circulation rates of 4–5 h−1, whereby both large units, which are positioned on the rear wall, realize a homogeneous dilution of the room air. This is achieved by an air outlet directed horizontally at a height above 2 m or diagonally towards the ceiling, which points into the room and partly to the sides. On the other hand, an air outlet directed exclusively to the sides or horizontally into the room at floor level to all sides achieves lower particle decay rates. To investigate the influence of the filter loading, three large APs were operated in a school for a period of one year (190 days with 8 h each). For the three APs, long-term operation leads to different changes in PNC reduction efficiency, ranging from −3% to −34%. It is found that not only the size of the prefilter and main filter has a significant influence, but also whether there is a prefilter bypass that negatively affects the loading level of the main filter. At the same time, it was shown that one type of AP, measuring the pressure drop across the filters and readjusting the fan, kept the circulation rate almost constant (up to −3%) over a year.
A New Extension of Optimal Auxiliary Function Method to Fractional Non-Linear Coupled ITO System and Time Fractional Non-Linear KDV System
Authors: Nawaz Rashid , Iqbal Aaqib , Bakhtiar Hina , Alhilfi Wissal Audah , Fewster-Young Nicholas , Ali Ali Hasan , Poțclean Ana Danca
Published: September 2023

In this article, we investigate the utilization of Riemann–Liouville’s fractional integral and the Caputo derivative in the application of the Optimal Auxiliary Function Method (OAFM). The extended OAFM is employed to analyze fractional non-linear coupled ITO systems and non-linear KDV systems, which feature equations of a fractional order in time. We compare the results obtained for the ITO system with those derived from the Homotopy Perturbation Method (HPM) and the New Iterative Method (NIM), and for the KDV system with the Laplace Adomian Decomposition Method (LADM). OAFM demonstrates remarkable convergence with a single iteration, rendering it highly effective. In contrast to other existing analytical approaches, OAFM emerges as a dependable and efficient methodology, delivering high-precision solutions for intricate problems while saving both computational resources and time. Our results indicate superior accuracy with OAFM in comparison to HPM, NIM, and LADM. Additionally, we enhance the accuracy of OAFM through the introduction of supplementary auxiliary functions.
Phenotypic Characterization of Female Carrier Mice Heterozygous for Tafazzin Deletion
Authors: Tomczewski Michelle V. , Chan John Z. , Al-Majmaie Duaa M. , Liu Ming Rong , Cocco Alex D. , Stark Ken D. , Strathdee Douglas , Duncan Robin E.
Published: September 2023

Barth syndrome (BTHS) is caused by mutations in tafazzin resulting in deficits in cardiolipin remodeling that alter major metabolic processes. The tafazzin gene is encoded on the X chromosome, and therefore BTHS primarily affects males. Female carriers are typically considered asymptomatic, but age-related changes have been reported in female carriers of other X-linked disorders. Therefore, we examined the phenotype of female mice heterozygous for deletion of the tafazzin gene (Taz-HET) at 3 and 12 months of age. Food intakes, body masses, lean tissue and adipose depot weights, daily activity levels, metabolic measures, and exercise capacity were assessed. Age-related changes in mice resulted in small but significant genotype-specific differences in Taz-HET mice compared with their female Wt littermates. By 12 months, Taz-HET mice weighed less than Wt controls and had smaller gonadal, retroperitoneal, and brown adipose depots and liver and brain masses, despite similar food consumption. Daily movement, respiratory exchange ratio, and total energy expenditure did not vary significantly between the age-matched genotypes. Taz-HET mice displayed improved glucose tolerance and insulin sensitivity at 12 months compared with their Wt littermates but had evidence of slightly reduced exercise capacity. Tafazzin mRNA levels were significantly reduced in the cardiac muscle of 12-month-old Taz-HET mice, which was associated with minor but significant alterations in the heart cardiolipin profile. This work is the first to report the characterization of a model of female carriers of heterozygous tafazzin deficiency and suggests that additional study, particularly with advancing age, is warranted.
Evaluation of the Effectiveness of Boron Neutron Capture Therapy with Iodophenyl-Conjugated closo-Dodecaborate on a Rat Brain Tumor Model
Authors: Fujikawa Yoshiki , Fukuo Yusuke , Nishimura Kai , Tsujino Kohei , Kashiwagi Hideki , Hiramatsu Ryo , Nonoguchi Naosuke , Furuse Motomasa , Takami Toshihiro , Hu Naonori , Miyatake Shin-Ichi , Takata Takushi , Tanaka Hiroki , Watanabe Tsubasa , Suzuki Minoru , Kawabata Shinji , Nakamura Hiroyuki , Wanibuchi Masahiko
Published: September 2023

High-grade gliomas present a significant challenge in neuro-oncology because of their aggressive nature and resistance to current therapies. Boron neutron capture therapy (BNCT) is a potential treatment method; however, the boron used by the carrier compounds—such as 4-borono-L-phenylalanine (L-BPA)—have limitations. This study evaluated the use of boron-conjugated 4-iodophenylbutanamide (BC-IP), a novel boron compound in BNCT, for the treatment of glioma. Using in vitro drug exposure experiments and in vivo studies, we compared BC-IP and BPA, with a focus on boron uptake and retention characteristics. The results showed that although BC-IP had a lower boron uptake than BPA, it exhibited superior retention. Furthermore, despite lower boron accumulation in tumors, BNCT mediated by BC-IP showed significant survival improvement in glioma-bearing rats compared to controls (not treated animals and neutrons only). These results suggest that BC-IP, with its unique properties, may be an alternative boron carrier for BNCT. Further research is required to optimize this potential treatment modality, which could significantly contribute to advancing the treatment of high-grade gliomas.
Recent Uses of Paper Microfluidics in Isothermal Nucleic Acid Amplification Tests
Authors: Reynolds Jocelyn , Loeffler Reid S. , Leigh Preston J. , Lopez Hannah A. , Yoon Jeong-Yeol
Published: September 2023

Isothermal nucleic acid amplification tests have recently gained popularity over polymerase chain reaction (PCR), as they only require a constant temperature and significantly simplify nucleic acid amplification. Recently, numerous attempts have been made to incorporate paper microfluidics into these isothermal amplification tests. Paper microfluidics (including lateral flow strips) have been used to extract nucleic acids, amplify the target gene, and detect amplified products, all toward automating the process. We investigated the literature from 2020 to the present, i.e., since the onset of the COVID-19 pandemic, during which a significant surge in isothermal amplification tests has been observed. Paper microfluidic detection has been used extensively for recombinase polymerase amplification (RPA) and its related methods, along with loop-mediated isothermal amplification (LAMP) and rolling circle amplification (RCA). Detection was conducted primarily with colorimetric and fluorometric methods, although a few publications demonstrated flow distance- and surface-enhanced Raman spectroscopic (SERS)-based detection. A good number of publications could be found that demonstrated both amplification and detection on paper microfluidic platforms. A small number of publications could be found that showed extraction or all three procedures (i.e., fully integrated systems) on paper microfluidic platforms, necessitating the need for future work.
Cross-Sensory EEG Emotion Recognition with Filter Bank Riemannian Feature and Adversarial Domain Adaptation
Authors: Gao Chenguang , Uchitomi Hirotaka , Miyake Yoshihiro
Published: September 2023

Emotion recognition is crucial in understanding human affective states with various applications. Electroencephalography (EEG)—a non-invasive neuroimaging technique that captures brain activity—has gained attention in emotion recognition. However, existing EEG-based emotion recognition systems are limited to specific sensory modalities, hindering their applicability. Our study innovates EEG emotion recognition, offering a comprehensive framework for overcoming sensory-focused limits and cross-sensory challenges. We collected cross-sensory emotion EEG data using multimodal emotion simulations (three sensory modalities: audio/visual/audio-visual with two emotion states: pleasure or unpleasure). The proposed framework—filter bank adversarial domain adaptation Riemann method (FBADR)—leverages filter bank techniques and Riemannian tangent space methods for feature extraction from cross-sensory EEG data. Compared with Riemannian methods, filter bank and adversarial domain adaptation could improve average accuracy by 13.68% and 8.36%, respectively. Comparative analysis of classification results proved that the proposed FBADR framework achieved a state-of-the-art cross-sensory emotion recognition performance and reached an average accuracy of 89.01% ± 5.06%. Moreover, the robustness of the proposed methods could ensure high cross-sensory recognition performance under a signal-to-noise ratio (SNR) ≥ 1 dB. Overall, our study contributes to the EEG-based emotion recognition field by providing a comprehensive framework that overcomes limitations of sensory-oriented approaches and successfully tackles the difficulties of cross-sensory situations.
Focus on Multidisciplinary Aspects of Sleep Medicine
Authors: Cicolin Alessandro , Ferini-Strambi Luigi
Published: September 2023

Sleep is an essential biological requirement for human life, alongside food, water, and air [...]
Efficient Brain Age Prediction from 3D MRI Volumes Using 2D Projections
Authors: Jönemo Johan , Akbar Muhammad Usman , Kämpe Robin , Hamilton J. Paul , Eklund Anders
Published: September 2023

Using 3D CNNs on high-resolution medical volumes is very computationally demanding, especially for large datasets like UK Biobank, which aims to scan 100,000 subjects. Here, we demonstrate that using 2D CNNs on a few 2D projections (representing mean and standard deviation across axial, sagittal and coronal slices) of 3D volumes leads to reasonable test accuracy (mean absolute error of about 3.5 years) when predicting age from brain volumes. Using our approach, one training epoch with 20,324 subjects takes 20–50 s using a single GPU, which is two orders of magnitude faster than a small 3D CNN. This speedup is explained by the fact that 3D brain volumes contain a lot of redundant information, which can be efficiently compressed using 2D projections. These results are important for researchers who do not have access to expensive GPU hardware for 3D CNNs.
Children’s Shyness, Frontal Brain Activity, and Anxiety in the Perioperative Context
Authors: Chow Cheryl H. T. , Poole Kristie L. , Xu Richard Y. , Sriranjan Jhanahan , Van Lieshout Ryan J. , Buckley Norman , Moffat Graeme , Schmidt Louis A.
Published: September 2023

Although preoperative anxiety affects up to 75% of children undergoing surgery each year and is associated with many adverse outcomes, we know relatively little about individual differences in how children respond to impending surgery. We examined whether patterns of anterior brain electrical activity (i.e., a neural correlate of anxious arousal) moderated the relation between children’s shyness and preoperative anxiety on the day of surgery in 70 children (36 girls, Mage = 10.4 years, SDage = 1.7, years, range 8 to 13 years) undergoing elective surgery. Shyness was assessed using self-report approximately 1 week prior to surgery during a preoperative visit (Time 1), preoperative anxiety was assessed using self-report, and regional EEG (left and right frontal and temporal sites) was assessed using a dry sensory EEG headband on the day of surgery (Time 2). We found that overall frontal EEG alpha power moderated the relation between shyness and self-reported preoperative anxiety. Shyness was related to higher levels of self-reported anxiety on the day of surgery for children with lower average overall frontal alpha EEG power (i.e., higher cortical activity) but not for children with higher average overall frontal alpha EEG power (i.e., lower cortical activity). These results suggest that the pattern of frontal brain activity might amplify some shy children’s affective responses to impending surgery. Findings also extend prior results linking children’s shyness, frontal brain activity, and anxiety observed in the laboratory to a real-world, ecologically salient environment.
Research Progress of Urban Park Microclimate Based on Quantitative Statistical Software
Authors: Lin Jiayi , Deng Yuqian , Chen Sibo , Li Kaiyuan , Ji Wenli , Li Weizhong
Published: September 2023

Urban parks, as an important component of urban green spaces, play a crucial role in improving the urban environment and enhancing residents’ quality of life. This review summarizes the main content and research progress of urban park microclimate studies through analysis and synthesis of relevant literature from academic databases such as Web of Science and Google Scholar. Using Citespace or VOSviewer for bibliometric analysis, we found that the number of academic papers on the urban park microclimate has been growing year by year. The research content primarily covers the monitoring and analysis of temperature, humidity, wind speed, and other indicators in urban parks, as well as the impact of park design and planning on the microclimate. Keyword analysis revealed that researchers have mainly focused on the cooling effects of the urban park microclimate, mitigation of the urban heat island effect, and improvement of air quality. In terms of research methods, a combination of field observations and simulation models is commonly employed, with data being analyzed and validated using mathematical and statistical methods. The research results indicate that well-designed and planned parks can significantly improve the microclimate environment, reduce temperatures, and provide comfortable climatic conditions in urban areas. Additionally, vegetation arrangements and water features in urban parks also contribute to microclimate regulation. Moreover, windbreak measures and cooling strategies in parks can help alleviate the urban heat island effect, enhance air quality, and promote the health of ecosystems. However, this review also identified some issues in urban park microclimate research, including limitations in research scope, methods, and practical applicability. Future studies could deepen the comprehensive understanding of the urban park microclimate and explore more effective strategies for park design and planning to optimize and enhance the microclimate environment. It is also important for researchers to continuously innovate in terms of research methods and verify the feasibility of practical applications to better address the challenges of urban development.
Hourly Heat Load Prediction for Residential Buildings Based on Multiple Combination Models: A Comparative Study
Authors: An Wenhan , Zhu Xiangyuan , Yang Kaimin , Kim Moon Keun , Liu Jiying
Published: September 2023

The accurate prediction of residential heat load is crucial for effective heating system design, energy management, and cost optimization. In order to further improve the prediction accuracy of the model, this study introduced principal component analysis (PCA), the minimum sum of squares of the combined prediction errors (minSSE), genetic algorithm (GA), and firefly algorithm (FA) into back propagation (BP) and ELMAN neural networks, and established three kinds of combined prediction models. The proposed methodologies are evaluated using real-world data collected from residential buildings over a period of one year. The obtained results of the PCA-BP-ELMAN, FA-ELMAN, and GA-BP models are compared with the neural network before optimization. The experimental results show that the combined prediction models have higher prediction accuracy. The Mean Absolute Percentage Error (MAPE) evaluation indices of the three combined models are distributed between 5.95% and 7.05%. The FA-ELMAN model is the combination model with the highest prediction accuracy, and its MAPE is 5.95%, which is 2.25% lower than the MAPE of an individual neural network. This research contributes to the field by providing a comprehensive and effective framework for residential heat load prediction, which can be valuable for building energy management and optimization.
G1 Dynamics at the Crossroads of Pluripotency and Cancer
Authors: Fleifel Dalia , Cook Jeanette Gowen
Published: September 2023

G1 cell cycle phase dynamics are regulated by intricate networks involving cyclins, cyclin-dependent kinases (CDKs), and CDK inhibitors, which control G1 progression and ensure proper cell cycle transitions. Moreover, adequate origin licensing in G1 phase, the first committed step of DNA replication in the subsequent S phase, is essential to maintain genome integrity. In this review, we highlight the intriguing parallels and disparities in G1 dynamics between stem cells and cancer cells, focusing on their regulatory mechanisms and functional outcomes. Notably, SOX2, OCT4, KLF4, and the pluripotency reprogramming facilitator c-MYC, known for their role in establishing and maintaining stem cell pluripotency, are also aberrantly expressed in certain cancer cells. In this review, we discuss recent advances in understanding the regulatory role of these pluripotency factors in G1 dynamics in the context of stem cells and cancer cells, which may offer new insights into the interconnections between pluripotency and tumorigenesis.
A Review of Biomarkers and Their Clinical Impact in Resected Early-Stage Non-Small-Cell Lung Cancer
Authors: Cao Weibo , Tang Quanying , Zeng Jingtong , Jin Xin , Zu Lingling , Xu Song
Published: September 2023

The postoperative survival of early-stage non-small-cell lung cancer (NSCLC) patients remains unsatisfactory. In this review, we examined the relevant literature to ascertain the prognostic effect of related indicators on early-stage NSCLC. The prognostic effects of the epidermal growth factor receptor (EGFR), anaplastic lymphoma kinase (ALK), mesenchymal–epithelial transition (MET), C-ros oncogene 1 (ROS1), or tumour protein p53 (TP53) alterations in resected NSCLC remains debatable. Kirsten rat sarcoma viral oncogene homologue (KRAS) alterations indicate unfavourable outcomes in early-stage NSCLC. Meanwhile, adjuvant or neoadjuvant EGFR-targeted agents can substantially improve prognosis in early-stage NSCLC with EGFR alterations. Based on the summary of current studies, resected NSCLC patients with overexpression of programmed death-ligand 1 (PD-L1) had worsening survival. Conversely, PD-L1 or PD-1 inhibitors can substantially improve patient survival. Considering blood biomarkers, perioperative peripheral venous circulating tumour cells (CTCs) and pulmonary venous CTCs predicted unfavourable prognoses and led to distant metastases. Similarly, patients with detectable perioperative circulating tumour DNA (ctDNA) also had reduced survival. Moreover, patients with perioperatively elevated carcinoembryonic antigen (CEA) in the circulation predicted significantly worse survival outcomes. In the future, we will incorporate mutated genes, immune checkpoints, and blood-based biomarkers by applying artificial intelligence (AI) to construct prognostic models that predict patient survival accurately and guide individualised treatment.