bluuebunny/crossref_metadata_2025 huggingface dataset:
Influence of Body Composition on Cardiorespiratory Fitness and Metabolic Markers in Physically Inactive Individuals with Insulin Resistance: An Observational Study
Authors: Azócar-Gallardo Jairo , Ojeda-Aravena Alex , Báez-San Martín Eduardo , Campos-Uribe Victor , González-Rojas Luis , Castillo Cerda María A. , García-García José Manuel
Published: February 2023

The aim of this study was to determine body composition influence on cardiorespiratory fitness and metabolic markers in physically inactive individuals with insulin resistance (IR). Nineteen overweight and obese (body mass index [BMI] 25.0–29.9 kg·m−2; ≥ 30.0 kg·m−2, respectively) patients diagnosed with IR (5 men and 14 women; age: 32.74 ± 10.07 years; BMI: 32.5 ± 4.60 kg·m−2). The body composition included BMI, fat mass, and fat-free mass. Cardiorespiratory fitness was measured by maximal oxygen uptake (VO2max). Metabolic markers included maximal fat oxidation, fasting glucose, and insulin. IR was determined by homeostatic model assessment (HOMA-IR). The results of the partial correlations (i.e., body mass, age, and sex) reported that fat-free mass, fat mass, and BMI were significantly correlated with VO2max. Additionally, the multiple linear regression model indicated that fat-free mass and BMI explained the variance of VO2max by 89%. However, no substantial correlations were reported between fat mass or fat-free mass with HOMA-IR, fasting glucose, or insulin. This study concluded that a higher percentage of fat-free mass and lower BMI is positively related to better cardiorespiratory fitness despite the IR status of the participants analyzed.
Evaluation of Early Age Concrete Pavement Strength by Combined Nondestructive Tests
Authors: Kosar Katelyn , Khazanovich Lev , Salles Lucio
Published: February 2023

During concrete pavement construction, comprehensive information on concrete strength development is necessary for knowledgeable scheduling decisions. To improve in situ strength estimation, nondestructive tests can be combined to maximize available information and increase collection efficiency. Ultrasonic testing has a higher accuracy in strength estimation for early age concrete and the external device allows for more data to be easily collected, while maturity testing can use temperature models to predict strength development. A procedure was created that combines these methods and their strength models in the laboratory for improved and increased field strength data. Using the procedure allows more data to be collected with greater accuracy and provides an adjustable, predicted strength development. This improves the efficiency of fast-track construction projects without resorting to costly alternatives by providing more information on strength development of in situ concrete than traditional strength testing or nondestructive methods individually.
Study of Local Fatigue Methods (TCD, N-SIF, and ESED) on Notches and Defects Related to Numerical Efficiency
Authors: Stoschka Michael , Horvath Michael , Fladischer Stefan , Oberreiter Matthias
Published: February 2023

The fatigue strength of structural components is strongly affected by notches and imperfections. Both can be treated similarly, as local notch fatigue strength methods can also be applied to interior defects. Even though Murakami’s √area approach is commonly used in the threshold-based fatigue design of single imperfections, advanced concepts such as the Theory of Critical Distances (TCD), Notch Stress Intensity Factors (N-SIF), or Elastic Strain Energy Density (ESED) methods provide additional insight into the local fatigue strength distribution of irregularly shaped defects under varying uniaxial load vectors. The latter methods are based on the evaluation of the elastic stress field in the vicinity of the notch for each single load vector. Thus, this work provides numerically efficient methods to assess the local fatigue strength by means of TCD, N-SIF, and ESED, targeting the minimization of the required load case count, optimization of stress field evaluation data points, and utilization of multi-processing. Furthermore, the Peak Stress Method (PSM) is adapted for large opening angles, as in the case of globular defects. In detail, two numerical strategies are devised and comprehensively evaluated, either using a sub-case-based stress evaluation of the defect vicinity with an unchanged mesh pattern and varying load vector on the exterior model region with optimized load angle stepping or by the invocation of stress and strain tensor transformation equations to derive load angle-dependent result superposition while leaving the initial mesh unaltered. Both methods provide numerically efficient fatigue post-processing, as the mesh in the evaluated defect region is retained for varying load vectors. The key functions of the fatigue strength assessment, such as the evaluation of appropriate planar notch radius and determination of notch opening angle for the discretized imperfections, are presented. Although the presented numerical methods apply to planar simulation studies, the basic methodology can be easily expanded toward spatial fatigue assessment.
Sensorless Current Pulsation Compensation in a Hybrid Energy Storage
Authors: Fatyga Karol , Zieliński Dariusz
Published: February 2023

This paper presents a dual active bridge DC/DC converter used as an AC current compensator in a hybrid energy storage application. The AC current in the DC link appears when a three-phase, four-wire inverter operates with unbalanced output currents—for example, when trying to compensate for grid voltage unbalance. This AC current has adverse effects on the operation of the electrochemical energy storage, and it should be compensated. To achieve this, a compensator is introduced into the DC link circuit of the inverter—a DC/DC converter with a capacitor bank. The DC/DC converter is responsible for compensating the AC pulsation by creating its own pulsation with the opposite phase. In the paper, the genesis of this pulsation is explained, and a compensation circuit is proposed along with a sensorless compensation algorithm. The algorithm is based on symmetrical decomposition and is used to generate a reference signal for the compensator. The numerical analysis of the algorithm is presented, and the operation of the compensator is verified on the laboratory bench.
Research on the Applicability of Transformer Model in Remote-Sensing Image Segmentation
Authors: Yu Minmin , Qin Fen
Published: February 2023

Transformer models have achieved great results in the field of computer vision over the past 2 years, drawing attention from within the field of remote sensing. However, there are still relatively few studies on this model in the field of remote sensing. Which method is more suitable for remote-sensing segmentation? In particular, how do different transformer models perform in the face of high-spatial resolution and the multispectral resolution of remote-sensing images? To explore these questions, this paper presents a comprehensive comparative analysis of three mainstream transformer models, including the segmentation transformer (SETRnet), SwinUnet, and TransUnet, by evaluating three aspects: a visual analysis of feature-segmentation results, accuracy, and training time. The experimental results show that the transformer structure has obvious advantages for the feature-extraction ability of large-scale remote-sensing data sets and ground objects, but the segmentation performance of different transfer structures in different scales of remote-sensing data sets is also very different. SwinUnet exhibits better global semantic interaction and pixel-level segmentation prediction on the large-scale Potsdam data set, and the SwinUnet model has the highest accuracy metrics for KAPPA, MIoU, and OA in the Potsdam data set, at 76.47%, 63.62%, and 85.01%, respectively. TransUnet has better segmentation results in the small-scale Vaihingen data set, and the three accuracy metrics of KAPPA, MIoU, and OA are the highest, at 80.54%, 56.25%, and 85.55%, respectively. TransUnet is better able to handle the edges and details of feature segmentation thanks to the network structure together built by its transformer and convolutional neural networks (CNNs). Therefore, TransUnet segmentation accuracy is higher when using a small-scale Vaihingen data set. Compared with SwinUnet and TransUnet, the segmentation performance of SETRnet in different scales of remote-sensing data sets is not ideal, so SETRnet is not suitable for the research task of remote-sensing image segmentation. In addition, this paper discusses the reasons for the performance differences between transformer models and discusses the differences between transformer models and CNN. This study further promotes the application of transformer models in remote-sensing image segmentation, improves the understanding of transformer models, and helps relevant researchers to select a more appropriate transformer model or model improvement method for remote-sensing image segmentation.
The Effect of Load Carrying on Gait Kinetic and Kinematic Variables in Soldiers with Patellofemoral Pain Syndrome
Authors: Dar Gali , Saposhnik Aviv , Finestone Aharon S. , Ayalon Moshe
Published: February 2023

Individuals suffering from patello-femoral pain syndrome (PFPS) exhibit altered gait parameters compared with healthy individuals. As soldiers carry heavy equipment, the extra load might further alter gait pattern. The aim of this study was to investigate the effect of load carrying on kinetic and kinematic variables in soldiers with PFPS compared with controls. The sample comprised 23 active-duty infantry soldiers (10 with bilateral/13 without bilateral PFPS, mean age: 20.4 (±0.5) years, height 179 (±5.8) cm, weight 76 (±6.9) kg). The participants walked barefoot on a 10 m walkway with and without loading equipment. The equipment added 50% to each participant’s body mass. Gait kinematic and kinetic variables were assessed by the VICON three-dimensional motion analysis system and two force plates. Weight carrying increased joint maximal angles, mean peak moments and double support and decreased single support and walk speed in both groups, without differences between groups (p > 0.05). The only difference between groups was in the hip adduction angle without a load (p < 0.05); no difference was observed while carrying the load. Kinematic and kinetic differences in gait were detected between weight and non-weight conditions, yet there was no effect of PFPS. Further studies with subjects performing different tasks are essential to examining the effect of PFPS and load among soldiers.
X-ray Free Electron Laser Accelerator Lattice Design Using Laser-Assisted Bunch Compression
Authors: Xu Haoran , Anisimov Petr M. , Carlsten Bruce E. , Duffy Leanne D. , Marksteiner Quinn R. , Robles River R.
Published: February 2023

We report the start-to-end modeling of our accelerator lattice design employing a laser-assisted bunch compression (LABC) scheme in an X-ray free electron laser (XFEL), using the proposed Matter-Radiation Interactions in Extremes (MaRIE) XFEL parameters. The accelerator lattice utilized a two-stage bunch compression scheme, with the first bunch compressor performing a conventional bulk compression enhancing the beam current from 20 A to 500 A, at 750 MeV. The second bunch compression was achieved by modulating the beam immediately downstream of the first bunch compressor by a laser with 1-μm wavelength in a laser modulator, accelerating the beam to the final energy of 12 GeV, and compressing the individual 1-μm periods of the modulated beam into a sequence of microbunches with 3-kA current spikes by the second bunch compressor. The LABC architecture presented had been developed based on the scheme of enhanced self-amplified spontaneous emission (ESASE), but operated in a disparate regime of parameters. Enabled by the novel technology of the cryogenic normal conducting radiofrequency photoinjector, we investigated an electron beam with ultra-low emittance at the starting point of the lattice design. Our work aimed at mitigating the well-known beam instabilities to preserve the beam emittance and suppress the energy spread growth.
Geostationary Precipitation Estimates by PDF Matching Technique over the Asia-Pacific and Its Improvement by Incorporating with Surface Data
Authors: Chen Yun-Lan , Chen Chia-Rong , Xie Pingping
Published: February 2023

An Infrared (IR)-passive microwave (PMW) blended technique is developed to derive precipitation estimates over the Asia-Pacific domain through calibrating the temperature of brightness blackbody from the Japanese Himawari-8 satellite to precipitation derived from the combined PMW retrievals (currently MWCOMB2x) based on the probability density function (PDF)-matching concept. Called IRQPE, the technique is modified and fine-tuned to better represent the spatially rapidly changing cloud–precipitation relationship over the target region with PDF-matching tables established over a refined spatial resolution of 0.5° lat/lon grid. The evaluation of the IRQPE shows broadly comparable performance to that of the CMORPH2 in detecting rainfall systems of large and medium-scales at a resolution of 1.0° degree. Rainfall variations from the two datasets over El Niño-Southern Oscillation and the Madden Julian Oscillation active convective centers show well consistency of each other, suggesting usefulness of the IRQPE in climate applications. Two approaches for regional improvements are explored by establishing the PDF tables for a further refined spatial resolution and by replacing the PMW-based precipitation ‘truth’ fields with the surface gauge data to overcome the shortcoming of PMW-based retrievals in capturing orographic rainfall over the Taiwan area. The results show significant improvements. The rainfall patterns of revised the IRQPE at a resolution of 0.1° degree on above the 5-day timescale correlate well with the Taiwan official surface ground truth called the QPESUMS, which is a gridded set of gauge-corrected Radar quantitative precipitation estimations. The root mean square error of the revised IRQPE on estimating the Taiwan overall land rainfall is close to Radar-derived rainfall accumulations on a 30-day time-scale.
A Theoretical Study of Scattering of e± by Tl Atom
Authors: Parvin Sunzida , Billah M. Masum , Khandker Mahmudul H. , Hossain M. Ismail , Haque M. M. , Shahmohammadi Beni Mehrdad , Watabe Hiroshi , Haque A. K. Fazlul , Uddin M. Alfaz
Published: February 2023

This article incorporates details of our calculations of the observable quantities for the scattering of electrons and positrons from a post transition metal Thallium (Tl), in the energy range of 1 eV ≤ Ei ≤ 1 MeV, using the relativistic Dirac partial wave (phase-shift) analysis employing a complex optical-potential. Absolute differential, integrated elastic and inelastic, transport, total ionization, and total cross sections and a thorough study of the critical minima in the elastic differential cross sections along with the associated angular positions of the maximum polarization points in the Sherman function are provided to study the collision dynamics. The optical potential model incorporates the interactions of the incident electron and/or positron with both the nucleus and the bound electrons of the target atom. In-depth analyses of the spin asymmetry, which are sensitive to phases related interference effect, brought on by the various ingredients of the lepton-atom interaction, are also presented. The performance of the current approach to explain the observations, with the exception of the extremely low energy domain, is shown by a comparison of the previous experimental and theoretical results on this target atom.
Monotonically Iterative Method for the Cantilever Beam Equations
Authors: Cui Yujun , Chen Huiling , Zou Yumei
Published: February 2023

In this paper, we consider the existence of extremal solutions for the nonlinear fourth-order differential equation. By use of a new comparison result, some sufficient conditions for the existence of extremal solutions are established by combining the monotone iterative technique and the methods of lower and upper solutions. Finally, an example is given to illustrate the validity of our main results.
Mathematical Modeling of the Tumor–Immune System with Time Delay and Diffusion
Authors: Cherraf Amina , Li Mingchu , Moulai-Khatir Anes , Hamidaoui Meryem
Published: February 2023

This paper proposes a partial differential equation model based on the model introduced by V. A. Kuznetsov and M. A. Taylor, which explains the dynamics of a tumor–immune interaction system, where the immune reactions are described by a Michaelis–Menten function. In this work, time delay and diffusion process are considered in order to make the studied model closer to reality. Firstly, we analyze the local stability of equilibria and the existence of Hopf bifurcation by using the delay as a bifurcation parameter. Secondly, we use the normal form theory and the center manifold reduction to determine the normal form of Hopf bifurcation for the studied model. Finally, some numerical simulations are provided to illustrate the analytic results. We show how diffusion has a significant effect on the dynamics of the delayed interaction tumor–immune system.
CTS-Net: A Segmentation Network for Glaucoma Optical Coherence Tomography Retinal Layer Images
Authors: Xue Songfeng , Wang Haoran , Guo Xinyu , Sun Mingyang , Song Kaiwen , Shao Yanbin , Zhang Hongwei , Zhang Tianyu
Published: February 2023

Optical Coherence Tomography (OCT) technology is essential to obtain glaucoma diagnostic data non-invasively and rapidly. Early diagnosis of glaucoma can be achieved by analyzing the thickness and shape of retinal layers. Accurate retinal layer segmentation assists ophthalmologists in improving the efficiency of disease diagnosis. Deep learning technology is one of the most effective methods for processing OCT retinal layer images, which can segment different retinal layers and effectively obtain the topological structure of the boundary. This paper proposes a neural network method for retinal layer segmentation based on the CSWin Transformer (CTS-Net), which can achieve pixel-level segmentation and obtain smooth boundaries. A Dice loss function based on boundary areas (BADice Loss) is proposed to make CTS-Net learn more features of edge regions and improve the accuracy of boundary segmentation. We applied the model to the publicly available dataset of glaucoma retina, and the test results showed that mean absolute distance (MAD), root mean square error (RMSE), and dice-similarity coefficient (DSC) metrics were 1.79 pixels, 2.15 pixels, and 92.79%, respectively, which are better than those of the compared model. In the cross-validation experiment, the ranges of MAD, RMSE, and DSC are 0.05 pixels, 0.03 pixels, and 0.33%, respectively, with a slight difference, which further verifies the generalization ability of CTS-Net.
Time- and Sex-Dependent Effects of Fingolimod Treatment in a Mouse Model of Alzheimer’s Disease
Authors: Bascuñana Pablo , Brackhan Mirjam , Möhle Luisa , Wu Jingyun , Brüning Thomas , Eiriz Ivan , Jansone Baiba , Pahnke Jens
Published: February 2023

Alzheimer’s disease (AD) is the most common cause of dementia. Fingolimod has previously shown beneficial effects in different animal models of AD. However, it has shown contradictory effects when it has been applied at early disease stages. Our objective was to evaluate fingolimod in two different treatment paradigms. To address this aim, we treated male and female APP-transgenic mice for 50 days, starting either before plaque deposition at 50 days of age (early) or at 125 days of age (late). To evaluate the effects, we investigated the neuroinflammatory and glial markers, the Aβ load, and the concentration of the brain-derived neurotrophic factor (BDNF). We found a reduced Aβ load only in male animals in the late treatment paradigm. These animals also showed reduced microglia activation and reduced IL-1β. No other treatment group showed any difference in comparison to the controls. On the other hand, we detected a linear correlation between BDNF and the brain Aβ concentrations. The fingolimod treatment has shown beneficial effects in AD models, but the outcome depends on the neuroinflammatory state at the start of the treatment. Thus, according to our data, a fingolimod treatment would be effective after the onset of the first AD symptoms, mainly affecting the neuroinflammatory reaction to the ongoing Aβ deposition.
Conversion of M1 Macrophages to Foam Cells: Transcriptome Differences Determined by Sex
Authors: Nambo-Venegas Rafael , Palacios-González Berenice , Mas-Oliva Jaime , Aurioles-Amozurrutia Ana Karen , Cruz-Rangel Armando , Moreno Abel , Hidalgo-Miranda Alfredo , Rodríguez-Dorantes Mauricio , Vadillo-Ortega Felipe , Xicohtencatl-Cortes Juan , Ruiz-Olmedo María Isabel , Reyes-Grajeda Juan Pablo
Published: February 2023

Background: M1 macrophages involved in pro-inflammatory processes can be induced by low-density lipoproteins (LDL), giving rise to foam cells. In the atheroma plaque, it has been identified that males present more advanced lesions associated with infiltration. Therefore, our study aims to investigate sex-related changes in the transcriptome of M1 macrophages during the internalization process of LDL particles. Methods: Peripheral blood mononuclear cells (PBMCs) from healthy male and female subjects were separated using Hystopaque, and monocytes were isolated from PBMCs using a positive selection of CD14+ cells. Cells were stimulated with LDL 10 µg/mL, and the transcriptional profile of M1 macrophages performed during LDL internalization was determined using a Clariom D platform array. Results: Chromosome Y influences the immune system and inflammatory responses in males expressing 43% of transcripts in response to LDL treatment. Males and females share 15 transcripts, where most correspond to non-coding elements involved in oxidative stress and endothelial damage. Conclusions: During LDL internalization, male monocyte-derived M1 macrophages display more marked proinflammatory gene expression. In contrast, female M1 macrophages display a more significant number of markers associated with cell damage.
Correspondence between Aortic and Arterial Stiffness, and Diastolic Dysfunction in Apparently Healthy Female Patients with Post-Acute COVID-19 Syndrome
Authors: Tudoran Cristina , Bende Felix , Bende Renata , Giurgi-Oncu Catalina , Dumache Raluca , Tudoran Mariana
Published: February 2023

(1) Background: Abnormally increased arterial and aortic stiffness (AS and AoS), which are often associated with diastolic dysfunction (DD), represent common alterations in COVID-19. In this study, we aimed to assess, by transthoracic echocardiography (TTE) and pulse-wave velocity (PWV), the frequency of these dysfunctions in patients with post-acute COVID-19 syndrome and to highlight potential correlations between their severity and multiple clinical and laboratory parameters. (2) Methods: In total, 121 women were included in our study, all of whom were younger than 55 and had been diagnosed with post-COVID-19 syndrome. Of those women, 67 also had metabolic syndrome (MS) (group A), whereas the other 54 did not (group B); 40 age-matched healthy subjects were used as controls (group C). (3) Results: Patients in group A had worse values of indexes characterizing AS and AoS and had more frequent DD compared to those from group B and group C (p < 0.0001). The statistical analysis evidenced significant associations between these indexes and the time that had elapsed since COVID-19 diagnosis, the factors that characterize the severity of the acute disease and those that specify MS. Multivariate regression analysis identified the following as the main independent predictors for DD: values of the AoS index, the C-reactive protein, and the triglyceride–glucose index. (4) Conclusions: Altered AS, AoS, and DD are common in patients with post-COVID-19 syndrome, especially with concurrent MS, and these parameters are apparently associated not only with the severity and time elapsed since COVID-19 diagnosis but also with MS.
Clinical Validation of GenBody COVID-19 Ag, Nasal and Nasopharyngeal Rapid Antigen Tests for Detection of SARS-CoV-2 in European Adult Population
Authors: Wegrzynska Karolina , Walory Jaroslaw , Charkiewicz Radoslaw , Lewandowska Marzena Anna , Wasko Izabela , Kozinska Aleksandra , Majewski Piotr , Baraniak Anna
Published: February 2023

Accurate and rapid identification of COVID-19 is critical for effective patient treatment and disease outcomes, as well as the prevention of SARS-CoV-2 transmission. Rapid antigen tests (RATs) for identifying SARS-CoV-2 are simpler, faster and less expensive than molecular assays. Any new product to be considered a medical device is subject to evaluation and data analysis to verify the in vitro diagnostic ability to achieve its intended purpose. Clinical validation of such a test is a prerequisite before clinical application. This study was a clinical validation on adult Europeans of GenBody COVID-19 Ag, nasal and nasopharyngeal RATs. A set of 103 positive and 301 negative from nose and nasopharynx samples confirmed by RT-qPCR were examined. The tests were safe to use and showed 100% specificity in both specimens, and high sensitivity of 94.17% (95%CI 87.75% to 97.83%) and 97.09% (95%CI 91.72% to 99.4%), respectively. The parameters were significantly better for samples with higher virus loads (the highest for CT ≤ 25). The GenBody COVID-19 Ag RATs are inexpensive (compared to RT-qPCR), reliable and rapid with high sensitivity and specificity, making them suitable for diagnosis and timely isolation and treatment of COVID-19 patients, contributing to the better control of virus spread.
Nonlinear Adaptive Optimal Controller Design for Anti-Angiogenic Tumor Treatment
Authors: Nath Nitendra , Kil Irfan , Hasirci Ugur , Groff Richard E. , Burg Timothy C.
Published: February 2023

Angiogenesis is an important process in tumor growth as it represents the regime when the tumor recruits blood vessels from the surrounding tissue to support further tumor growth. Anti-angiogenic treatments aim to shrink the tumor by interrupting the vascularization of the tumor; however, the anti-angiogenic agents are costly and the tumor response to these agents is nonlinear. Simple dosing schemes, e.g., a constant dose, may yield higher cost or lower efficacy than an approach that considers the tumor system dynamics. Hence, in this study, the administration of anti-angiogenic treatment is considered as a nonlinear control problem. The main aim of the controller design is to optimize the anti-angiogenic tumor therapy, specifically, to minimize the tumor volume and drug dose. Toward this aim, two nonlinear optimal controllers are presented. The first controller ensures exponential tracking of a desired, optimal tumor volume profile under the assumption that all parameters in the system model are known. The second controller, on the other hand, assumes all the parameters are unknown and provides asymptotic tracking. Both controllers take pharmacokinetics and pharmacodynamics into account, as well as the carrying capacity of the vascular network. Lyapunov based arguments are used to design the controllers, using stability arguments, and numerical simulation results are presented to demonstrate the effectiveness of the proposed method.
AgRP Neuron-Specific Ablation Represses Appetite, Energy Intake, and Somatic Growth in Larval Zebrafish
Authors: Lin Chiu-Ya , Yeh Kun-Yun , Lai Hsin-Hung , Her Guor Mour
Published: February 2023

Neuronal circuits regulating appetite are dominated by arcuate nucleus neurons, which include appetite-promoting and -suppressing neurons that release the orexigenic neuropeptide agouti-related protein (AgRP) and anorexigenic neuropeptide pro-opiomelanocortin, respectively, to compete for melanocortin receptors to modulate feeding behavior. In this study, we expressed novel agrp promoters, including different lengths of the 5’ flanking regions of the agrp gene (4749 bp) in the zebrafish genome. We used the agrp promoter to derive the enhanced green fluorescent protein (EGFP)-nitroreductase (NTR) fusion protein, allowing expression of the green fluorescence signal in the AgRP neurons. Then, we treated the transgenic zebrafish AgRP4.7NTR (Tg [agrp-EGFP-NTR]) with metronidazole to ablate the AgRP neurons in the larvae stage and observed a decline in their appetite and growth. The expression of most orexigenic and growth hormone/insulin-like growth factor axis genes decreased, whereas that of several anorexigenic genes increased. Our findings demonstrate that AgRP is a critical regulator of neuronal signaling for zebrafish appetite and energy intake control. Thus, AgRP4.7NTR can be used as a drug-screening platform for therapeutic targets to treat human appetite disorders, including obesity. Furthermore, the unique agrp promoter we identified can be a powerful tool for research on AgRP neurons, especially AgRP neuron-mediated pathways in the hypothalamus, and appetite.
Electrochemical Impedance Immunoassay for ALS-Associated Neurofilament Protein: Matrix Effect on the Immunoplatform
Authors: Adil Omair , Shamsi Mohtashim H.
Published: February 2023

Amyotrophic Lateral Sclerosis (ALS) is a neurodegenerative disorder, which has complex diagnostic steps. Electrochemical immunoassays may make the diagnosis simpler and faster. Here, we present the detection of ALS-associated neurofilament light chain (Nf-L) protein through an electrochemical impedance immunoassay on reduced graphene oxide (rGO) screen-printed electrodes. The immunoassay was developed in two different media, i.e., buffer and human serum, to compare the effect of the media on their figures of merit and calibration models. The label-free charge transfer resistance (RCT) of the immunoplatform was used as a signal response to develop the calibration models. We found that exposure of the biorecognition layer to human serum improved the impedance response of the biorecognition element with significantly lower relative error. Moreover, the calibration model obtained in the human serum environment has higher sensitivity and a better limit of detection (0.087 ng/mL) than the buffer medium (0.39 ng/mL). The analyses of the ALS patient samples show that concentrations obtained from the buffer-based regression model was higher than the serum-based model. However, a high Pearson correlation (r = 1.00) between the media suggests that concentration in one medium may be useful to predict the concentration in the other medium. Moreover, the Nf-L concentration appears to increase with age in both male and female groups, while overall higher Nf-L was found in the male group than the female group.
ERP Indicators of Phonological Awareness Development in Children: A Systematic Review
Authors: Stekić Katarina , Ilić Olivera , Ković Vanja , Savić Andrej M.
Published: February 2023

Phonological awareness is the ability to correctly recognize and manipulate phonological structures. The role of phonological awareness in reading development has become evident in behavioral research showing that it is inherently tied to measures of phonological processing and reading ability. This has also been shown with ERP research that examined how phonological processing training can benefit reading skills. However, there have not been many attempts to systematically review how phonological awareness itself is developed neurocognitively. In the present review, we screened 224 papers and systematically reviewed 40 papers that have explored phonological awareness and phonological processing using ERP methodology with both typically developing and children with reading problems. This review highlights ERP components that can be used as neurocognitive predictors of early developmental dyslexia and reading disorders in young children. Additionally, we have presented how phonological processing is developed neurocognitively throughout childhood, as well as which phonological tasks can be used to predict the development of phonological awareness prior to developing reading skills. Neurocognitive measures of early phonological processing can serve as supplemental diagnostic sources to behavioral measures of reading abilities because they show different aspects of phonological sensitivity when compared to behavioral measures.
Validating the Chinese Version of the Personal Accountability Measure for Assessing Teachers’ Perceptions and Experiences of Teacher Accountability in China
Authors: Tsang Kwok Kuen , Zhang Wanying , Teng Yuan , Song Huan
Published: February 2023

The study aims to validate the Chinese version of Personal Accountability Measure (PAM-Ch), which is used to assess the subjective aspect of teacher accountability, by surveying 1146 teachers enrolled in professional development courses offered by a public university in Beijing. The validation process involved two phases. First, the samples were randomly divided into three subgroups—for subgroup 1 (n = 390), exploratory factor analysis was computed; for subgroup 2 (n = 359), confirmatory factor analysis (CFA) was computed; and, for subgroup 3 (n = 381), a new CFA was performed for cross-validation. Second, Cronbach’s α, composite reliability (CR), average variance extracted (AVE), maximum shared variance (MSV), and average shared variance (ASV) were calculated for testing the reliability and validity. Throughout the process, three measurement models were tested for the adaptation of the PAM-Ch in this study. The results found that Model 2 was the best fit for the data, whose factor loadings ranged from 0.72–0.95 for internal accountability (factor 1) and 0.75–0.89 for external accountability (factor 2). The CRs of these two factors were 0.963 and 0.916, respectively, and the AVE values were 0.790 and 0.645, respectively, indicating that the PAM-Ch is a reliable and valid measure.
A Network Analysis-Driven Sequential Mediation Analysis of Students’ Perceived Classroom Comfort and Perceived Faculty Support on the Relationship between Teachers’ Cognitive Presence and Students’ Grit—A Holistic Learning Approach
Authors: Dughi Tiberiu , Rad Dana , Runcan Remus , Chiș Roxana , Vancu Gabriela , Maier Roxana , Costin Alina , Rad Gavril , Chiș Sabin , Uleanya Chinaza , Mihaela Macovei Crenguța
Published: February 2023

The interaction between teachers and students is critical to the learning process. Student success and learner satisfaction have consistently improved in educational situations where instructors and students connect frequently and meaningfully. The Community of Inquiry (CoI) framework, as well as the sense of belonging concept, have received a significant amount of attention from researchers investigating online learning since its debut. The current study focuses on the CoI framework in general, and in particular on studies on teaching, social, and cognitive presences in connection to students’ feeling of belonging and grit enhancement. This research investigated the opinion of 310 students at the Aurel Vlaicu University of Arad regarding their satisfaction with their teachers’ presences, their academic sense of belonging, and their grit. Our methodology followed an innovative approach. First, we employed a network analysis on all subscales’ mean scores, and then we performed a sequential mediation analysis based on both the network analysis results and the conclusions from the literature review. We tested whether students’ perceived classroom comfort and perceived faculty support sequentially mediated the relationship between teacher’s cognitive presence and students’ grit. According to the scientific literature, teacher’s cognitive presence consists of four fundamental categories: triggering events, exploration, integration, and resolution, which specifically the validation of knowledge by cooperation and reflection in a community of inquiry. We further tested if sense of belonging might mediate the relationship between teachers’ cognitive presence and students’ grit. The results show that students’ perceived classroom comfort and perceived faculty support partially and significantly sequentially mediate the relationship between teachers’ cognitive presence triggering events and students’ grit. The results are then further used to suggest possible recommendations for designing holistic learning environments in Romanian higher education institutions.
Effects of Core Training on Sport-Specific Performance of Athletes: A Meta-Analysis of Randomized Controlled Trials
Authors: Dong Kuan , Yu Tenghao , Chun Buongo
Published: February 2023

Improving athletes’ performance is a major topic of interest in studies on competitive sports. Core training has been used as a training method in daily life and rehabilitation, and recently, in competitive sports, with positive results. Previous experimental studies showed that core training can improve the fitness level of athletes (e.g., balance, core stability, etc.), but offer no consistent conclusions on whether it can improve sport-specific performance. The purpose of this study was to investigate the effect of core training on the sport-specific performance of athletes through a meta-analysis. Relevant studies on randomized controlled trials were selected, and we calculated the effect size using standardized mean difference values and the random effects model. Results showed that core training had almost no effect on athletes’ power and speed, while agility showed a medium effect size but no statistical significance. On the other hand, there was a large effect on general athletic performance, such as core endurance and balance. Consequently, core training had a great effect on the core endurance and balance of athletes, but little effect on sport-specific performance. This result implies that more elaborate core training programs should be designed to improve the sport-specific performance of athletes.
Near Real-Time 3D Reconstruction and Quality 3D Point Cloud for Time-Critical Construction Monitoring
Authors: Liu Zuguang , Kim Daeho , Lee Sanghyun , Zhou Li , An Xuehui , Liu Meiyin
Published: February 2023

Improving the rapidity of 3D reconstruction is vital for time-critical construction tasks such as progress monitoring and hazard detection, but the majority of construction studies in this area have focused on improving its quality. We applied a Direct Sparse Odometry with Loop Closure (LDSO)-based 3D reconstruction method, improving the existing algorithm and tuning its hyper-parameter settings, to achieve both near real-time operation and quality 3D point cloud simultaneously. When validated using a benchmark dataset, the proposed method showed notable improvement in 3D point cloud density, as well as loop closure robustness, compared to the original LDSO. In addition, we conducted a real field test to validate the tuned LDSO’s accuracy and speed at both object and site scales, where we demonstrated our method’s near real-time operation and capability to produce a quality 3D point cloud comparable to that of the existing method. The proposed method improves the accessibility of the 3D reconstruction technique, which in turn helps construction professionals monitor their jobsite safety and progress in a more efficient manner.
Impacts of Building Microenvironment on Energy Consumption in Office Buildings: Empirical Evidence from the Government Office Buildings in Guangdong Province, China
Authors: Li Zhaoji , Peng Shihong , Cai Weiguang , Cao Shuangping , Wang Xia , Li Rui , Ma Xianrui
Published: February 2023

Social progress and economic development has resulted in the need to focus on the impacts of building microenvironment on the energy consumption in office buildings. The concept of a building’s microenvironment was introduced to understand the local microclimate around a building that is formed by the surrounding urban green spaces, the distribution of roads, and building proximity. For this research, we adopted a regression analysis to quantify the impacts of building microenvironment on energy consumption in office buildings. Taking the government office buildings of Guangdong Province as an example, we measured the building microenvironment through the urban green space density, road density, and number of points of interest (POI) around the buildings. The results showed that when the green space density increased by one unit, the energy consumption in government office buildings was reduced by 0.277%. Moreover, an increase of 1% in road density and in the number of POI increased the energy consumption in government office buildings by 0.288% and 0.048%, respectively. Furthermore, we discussed the heterogeneous impacts of building microenvironment on the energy consumption in government office buildings at varying scale levels. Green space and road density had less impact on the energy consumption in larger buildings, whereas the number of POI had no significant impact on small-scale buildings but did have a significant impact on large-scale buildings. There were also some limitations in the study. The data were limited to government office buildings, and did not include panel data, as well as it lacked building characteristics such as orientation, floor height, and building materials. In addition, it was impossible to evaluate the impacts of meteorological factors such as wind speed and thermal radiation on energy consumption in buildings. Nonetheless, our study demonstrates that energy-aware urban planning and design have the potential to unlock energy efficiency for cities worldwide.
The Effect of Sustainable and Natural Looking on Perceived Aesthetics and Eco-Friendliness in Building Material Evaluation
Authors: Zhang Yaqi , Song Yao , Luo Jing
Published: February 2023

With the development of material synthesis technology, many artificial materials imitating natural materials have emerged in the construction industry. The processing technology of these materials’ surface imitating natural texture is becoming more and more realistic. Some materials are not made of sustainable material but use natural textures to imitate natural materials, attempting to bring users a sense of being close to nature and ecology to attract consumers to use it. However, the intention of use still depends on the user’s other factors like health, aesthetics, and environmental friendliness of the material. Therefore, the challenge for material manufacturers and designers is to understand people’s perceptions of these materials to increase their acceptance by users. This paper aims to investigate the user’s perception of materials (sustainable-unsustainable) to evaluate their perception of naturalness, environmental friendliness, and aesthetics through the visual senses. A total of 112 participants participated in the experiment which was divided into two groups (professional architects and non-professionals). The judgment of non-professionals on the environmental protection of materials imitating natural skin is relatively accurate, which is almost consistent with the judgment of professionals. Results show the importance of maintaining the naturalness of the surface texture in the material, which can enhance the user’s demand for a natural aesthetic feeling. Therefore, it is important to maintain the naturalness of surface texture in the process of material surface treatment. Users’ natural perception of materials will affect their aesthetic perception of materials.
Combining Breast Cancer Risk Prediction Models
Authors: Guan Zoe , Huang Theodore , McCarthy Anne Marie , Hughes Kevin , Semine Alan , Uno Hajime , Trippa Lorenzo , Parmigiani Giovanni , Braun Danielle
Published: February 2023

Accurate risk stratification is key to reducing cancer morbidity through targeted screening and preventative interventions. Multiple breast cancer risk prediction models are used in clinical practice, and often provide a range of different predictions for the same patient. Integrating information from different models may improve the accuracy of predictions, which would be valuable for both clinicians and patients. BRCAPRO is a widely used model that predicts breast cancer risk based on detailed family history information. A major limitation of this model is that it does not consider non-genetic risk factors. To address this limitation, we expand BRCAPRO by combining it with another popular existing model, BCRAT (i.e., Gail), which uses a largely complementary set of risk factors, most of them non-genetic. We consider two approaches for combining BRCAPRO and BCRAT: (1) modifying the penetrance (age-specific probability of developing cancer given genotype) functions in BRCAPRO using relative hazard estimates from BCRAT, and (2) training an ensemble model that takes BRCAPRO and BCRAT predictions as input. Using both simulated data and data from Newton-Wellesley Hospital and the Cancer Genetics Network, we show that the combination models are able to achieve performance gains over both BRCAPRO and BCRAT. In the Cancer Genetics Network cohort, we show that the proposed BRCAPRO + BCRAT penetrance modification model performs comparably to IBIS, an existing model that combines detailed family history with non-genetic risk factors.
Similarities and Differences in the Protein Composition of Cutaneous Melanoma Cells and Their Exosomes Identified by Mass Spectrometry
Authors: Surman Magdalena , Jankowska Urszula , Wilczak Magdalena , Przybyło Małgorzata
Published: February 2023

Intercellular transport of proteins mediated by extracellular vesicles (EVs)—exosomes and ectosomes—is one of the factors facilitating carcinogenesis. Therefore, the research on protein cargo of melanoma-derived EVs may provide a better understanding of the mechanisms involved in melanoma progression and contribute to the development of alternative biomarkers. Proteomic data on melanoma-derived EVs are very limited. The shotgun nanoLC-MS/MS approach was applied to analyze the protein composition of primary (WM115, WM793) and metastatic (WM266-4, WM1205Lu) cutaneous melanoma cells and exosomes released by them. All cells secreted homogeneous populations of exosomes that shared a characteristic set of proteins. In total, 3514 and 1234 unique proteins were identified in melanoma cells and exosomes, respectively. Gene ontology analysis showed enrichment in several cancer-related categories, including cell proliferation, migration, negative regulation of apoptosis, and angiogenesis. The obtained results broaden our knowledge on the role of selected proteins in exosome biology, as well as their functional role in the development and progression of cutaneous melanoma. The results may also inspire future studies on the clinical potential of exosomes.
Extracellular Vesicles in Colorectal Cancer: From Tumor Growth and Metastasis to Biomarkers and Nanomedications
Authors: Kotelevets Larissa , Chastre Eric
Published: February 2023

Colorectal cancer (CRC) is a leading public health concern due to its incidence and high mortality rates, highlighting the requirement of an early diagnosis. Evaluation of circulating extracellular vesicles (EVs) might constitute a noninvasive and reliable approach for CRC detection and for patient follow-up because EVs display the molecular features of the cells they originate. EVs are released by almost all cell types and are mainly categorized as exosomes originating from exocytosis of intraluminal vesicles from multivesicular bodies, ectosomes resulting from outward budding of the plasma membrane and apoptotic bodies’ ensuing cell shrinkage. These vesicles play a critical role in intercellular communications during physiological and pathological processes. They facilitate CRC progression and premetastatic niche formation, and they enable transfer of chemotherapy resistance to sensitive cells through the local or remote delivery of their lipid, nucleic acid and protein content. On another note, their stability in the bloodstream, their permeation in tissues and their sheltering of packaged material make engineered EVs suitable vectors for efficient delivery of tracers and therapeutic agents for tumor imaging or treatment. Here, we focus on the physiopathological role of EVs in CRCs, their value in the diagnosis and prognosis and ongoing investigations into therapeutic approaches.