bluuebunny/crossref_metadata_2025 huggingface dataset:
A Simple and Inexpensive Method to Gain Diatom Absolute Abundances from Permanent Mounts in Hydrobiological and Paleoecological Research
Authors: Cantonati Marco , Cid-Rodríguez María , Rossi Floriana , Leira Manel
Published: May 2023

Here, we describe and discuss a method based on microscopical field of view (FOV) area to estimate diatom absolute abundances (densities or concentrations), and we statistically verify its reliability, also comparing it to another commonly used method (microspheres). To test the new method, we purposely performed replicate counts, both with the FOV and with the microsphere method, on both subfossil and recent material (samples) from mires. Intraclass correlation (ICC) revealed a high degree of agreement between the measurements obtained for the replicates with each of the two methods, suggesting that both are reliable for measuring diatom valve concentrations. However, the FOV consistently overestimated diatom absolute abundances, as compared to the microsphere method, and the ICC value used to assess the reliability of the two methods combined suggested that the two methods cannot be used interchangeably. The FOV method is relatively simple, has a lower cost, wider applicability, higher resolution, and warrants compatibility with existing datasets. However, there may also be drawbacks, such as the potential for sample distortion during the concentration process. Therefore, it is important to carefully evaluate the strengths and limitations of the different methods before adopting one for specific research or applied questions.
Failure Identification Method and LMI-Based Control System for Small Spacecraft
Authors: Ruggiero Dario , Carnevaletti Niccolò , Capello Elisa , Park Hyeongjun
Published: May 2023

This study aimed to design a linear matrix inequality (LMI)-based robust control system and a failure identification method for small spacecraft. The key feature of the proposed method is its capability to withstand failure in the actuation system by means of the observer and controller gain definition. An effective approach for withstanding failure is required due to the small capabilities of the momentum exchange device (MED) and the system’s sensitivity to external perturbations. Passive fault-tolerant approaches can be included in the design process of the control algorithm. In particular, the main objective of this study was the design of an H∞ controller that started from an LMI formulation and considered the parametric uncertainties and matched failure of the actuation system. In addition, a fault detection method based on sliding mode observers was proposed to include an active disturbance correction algorithm and improve the system robustness and performance during spacecraft stabilization. The closed-loop system was evaluated for different initial conditions, including attitude positions that are far from the desired condition. The effectiveness of the proposed approach was demonstrated using extensive simulations that considered a pyramidal actuation configuration and hardware constraints.
Retrospective-Based Deep Q-Learning Method for Autonomous Pathfinding in Three-Dimensional Curved Surface Terrain
Authors: Han Qidong , Feng Shuo , Wu Xing , Qi Jun , Yu Shaowei
Published: May 2023

Path planning in complex environments remains a challenging task for unmanned vehicles. In this paper, we propose a decoupled path-planning algorithm with the help of a deep reinforcement learning algorithm that separates the evaluation of paths from the planning algorithm to facilitate unmanned vehicles in real-time consideration of environmental factors. We use a 3D surface map to represent the path cost, where the elevation information represents the integrated cost. The peaks function simulates the path cost, which is processed and used as the algorithm’s input. Furthermore, we improved the double deep Q-learning algorithm (DDQL), called retrospective-double DDQL (R-DDQL), to improve the algorithm’s performance. R-DDQL utilizes global information and incorporates a retrospective mechanism that employs fuzzy logic to evaluate the quality of selected actions and identify better states for inclusion in the memory. Our simulation studies show that the proposed R-DDQL algorithm has better training speed and stability compared to the deep Q-learning algorithm and double deep Q-learning algorithm. We demonstrate the effectiveness of the R-DDQL algorithm under both static and dynamic tasks.
Vertical Occlusal Dimension Changes of Complete Dentures between Autoclave and Traditional Processing Techniques
Authors: Atallah Samer , Salloum Alaa , Kharouf Naji
Published: May 2023

The aim of the present in vitro study was to investigate the effect of using an autoclave with three different programs and the traditional water bath method (short cycle) on the changes in the vertical occlusal dimension of the complete acrylic dentures. Forty complete acrylic dentures were divided into four groups: G1, dentures were polymerized by water bath method (short cycle for 90 min at 74 °C and then 30 min at 100 °C); G2, dentures were polymerized with an autoclave (134 °C/2.1 bar/10 min); G3, dentures were polymerized with an autoclave (121 °C/1.1 bar/20 min); and G4, dentures were polymerized with an autoclave (121 °C/1.1 bar/5 min). The vertical occlusal dimension of the dentures was measured before and after the polymerization process. The difference between the initial and final measurements expressed the change in the vertical occlusal dimension. Data were statistically analyzed by t-test and one-way ANOVA test. Statistically significant lower vertical dimension changes were detected in G1 (0.703 ± 0.078 mm) compared to the other groups (p < 0.05), whilst statistically greater changes were detected in G4 (1.263 ± 0.063 mm) compared to the other groups. No statistically significant differences were found between G2 (0.844 ± 0.061 mm) and G3 (0.88 ± 0.059 mm) (p > 0.05). Within the limitations of the present in vitro study, it can be concluded that all polymerization methods increase the vertical occlusal dimension of complete acrylic dentures. The increase in the vertical occlusal dimension in Groups 1, 2 and 3 was less than 1 mm which is clinically acceptable and can be overcome by selective abrasion. Therefore, the traditional curing technique using a water bath and the autoclave methods using two settings (134 °C/2.1 bar/10 min or 121 °C/1.1 bar/20 min) could be used for the complete acrylic denture with acceptable augmentation in the vertical occlusal dimension. In contrast, the method used in G4 increases the vertical occlusal dimension by more than 1 mm, which is not clinically acceptable.
Deep-Learning-Powered GRU Model for Flight Ticket Fare Forecasting
Authors: Degife Worku Abebe , Lin Bor-Shen
Published: May 2023

Forecasting flight fares is a critical task in the rapidly expanding civil aviation industry and involves numerous factors. However, traditional airfare prediction systems are ineffective due to the complex and nonlinear relationships of multiple factors, which are not able to accurately account for the impact of different attributes such as time period. To tackle these issues, in this study, we proposed a novel approach that utilizes a deep-learning model, specifically, the Gated Recurrent Unit (GRU), by incorporating 44 decision features. The proposed model is able to capture the intricate relationships between various factors effectively and predict air ticket prices with high accuracy. In the experiments, it was found that the GRU model significantly outperforms not only classic machine learning models but also the MLP and LSTM in terms of assessment indicators of mean absolute error (MAE), root mean square error (RMSE), and coefficient of determination (R2). The GRU model is thus promising concerning the fare prediction of flight tickets.
Research on Magnetic Coupling Flywheel Energy Storage Device for Vehicles
Authors: Ji Peng , Nie Wei-Wen , Liu Jia-Lu
Published: May 2023

With the increasing pressure on energy and the environment, vehicle brake energy recovery technology is increasingly focused on reducing energy consumption effectively. Based on the magnetization effect of permanent magnets, this paper presents a novel type of magnetic coupling flywheel energy storage device by combining flywheel energy storage with magnetic coupling technology. As a high-efficiency energy storage device, it has the advantages of low energy consumption, low vibration, low noise and easy maintenance. In this paper, firstly, the structural characteristics and working process of vehicle brake energy recovery systems are analyzed, and experiments regarding the transmission and efficiency performance are carried out for key components; then a reasonable control strategy is formulated according to the principle of energy recovery; finally, the speed, acceleration, recovery energy and other parameters are analyzed based on the New European Driving Cycle (NEDC) working conditions. The results show that the energy recovery efficiency reaches 35.59%, which verifies the usability of the device.
Investigation of Text-Background Lightness Combination on Visual Clarity Using a Head-Up Display under Various Surround Conditions and Different Age Groups
Authors: Huang Hsin-Pou , Li Hung-Chung , Wei Minchen , Li Guan-Hong
Published: May 2023

Up until now, head-up displays (HUDs) have been installed in front of the driver’s seat to provide drivers with auxiliary information. It may be used in various surroundings, ranging from very dark to very bright environments, such as daylight. A suitable text-background lightness combination can improve the driver’s visual clarity and efficiency when identifying displayed information to raise driving safety. Although many kinds of HUDs are designed to improve visual clarity by adjusting brightness, few studies have investigated the influence of the text-background lightness combination of a HUD on visibility, especially as the lighting level of the driving condition changes dramatically. In the study, 60 observers, comprising 20 young, 20 middle-aged, and 20 older participants, evaluated the visual clarity of 20 text-background lightness combinations on a HUD using paired comparison methods under dark and daylight surroundings (i.e., 300, 1500, and 9000 lx conditions). As a result, the combination of white text on a black background and black text on a white background presented the most significant preference and the best visual clarity under dark and daylight surroundings, respectively, improving visual safety when driving.
Comparison between Machine Learning and Deep Learning Approaches for the Detection of Toxic Comments on Social Networks
Authors: Bonetti Andrea , Martínez-Sober Marcelino , Torres Julio C. , Vega Jose M. , Pellerin Sebastien , Vila-Francés Joan
Published: May 2023

The way we communicate has been revolutionised by the widespread use of social networks. Any kind of online message can reach anyone in the world almost instantly. The speed with which information spreads is undoubtedly the strength of social networks, but at the same time, any user of these platforms can see how toxic messages spread in parallel with likes, comments and ratings about any person or entity. In such cases, the victim feels even more helpless and defenceless as a result of the rapid spread. For this reason, we have implemented an automatic detector of toxic messages on social media. This allows us to stop toxicity in its tracks and protect victims. In particular, the aim of the survey is to demonstrate how traditional Machine Learning methods of Natural Language Processing (NLP) work on equal terms with Deep Learning methods represented by a Transformer architecture and characterised by a higher computational cost. In particular, the paper describes the results obtained by testing different supervised Machine Learning classifiers (Logistic Regression, Random Forest and Support Vector Machine) combined with two topic-modelling techniques of NLP, (Latent Semantic Analysis and Latent Dirichlet Allocation). A pre-trained Transformer named BERTweet was also tested. All models performed well in this task, so much so that values close to or above 90% were achieved in terms of the F1 score evaluation metric. The best result achieved by Transformer BERTweet, 91.40%, was therefore not impressive in this context, as the performance gains are too small compared to the computational overhead.
A Reputation-Based Collaborative User Recruitment Algorithm in Edge-Aided Mobile Crowdsensing
Authors: Liu Yang , Li Yong , Cheng Wei , Wang Weiguang , Yang Junhua
Published: May 2023

Mobile CrowdSensing (MCS) has become a convenient method for many Internet of Things (IoT) applications in urban scenarios due to the full utilization of the mobility of people and the powerful capabilities of their intelligent devices. Nowadays, edge computing has been introduced into MCS to reduce the time delays and computational complexity in cloud platforms. To improve task completion and coverage rates, how to design a reasonable user recruitment algorithm to find suitable users and take full advantage of edge nodes has raised huge challenges for Mobile CrowdSensing. In this study, we propose a Reputation-based Collaborative User Recruitment algorithm (RCUR) under a certain budget in an edge-aided Mobile CrowdSensing system. We first introduce edge computing into MCS and build an edge-aided MCS system in urban scenarios. Moreover, we analyze the influence of user reputation on user recruitment. Then we establish a user reputation module to deduce the user reputation equation by combining the user’s past reputation score with an instantaneous reputation score. Finally, we utilize the sensing ability of edge nodes and design a collaborative sensing method. We use the greedy method to help choose the appropriate users for the tasks. Simulation results compared with the other three algorithms prove that our RCUR approach can significantly achieve better performance in task completion rate and task coverage rate.
Primary Stability Assessment of Conical Implants in Under-Prepared Sites: An In Vitro Study in Low-Density Polyurethane Foams
Authors: Comuzzi Luca , Tumedei Margherita , Covani Ugo , Romasco Tea , Petrini Morena , Montesani Lorenzo , Piattelli Adriano , Di Pietro Natalia
Published: May 2023

Bone characteristics, the implant macrogeometry, and the drilling technique are considered the main important factors to obtain a good implant primary stability (PS). Indeed, although it is known that implant placement in poor bone sites increases the possibility of implant failure, several surgical procedures have been proposed to improve PS, such as site under-preparation. Hence, this in vitro study aimed to evaluate the insertion torque (IT), removal torque (RT), and resonance frequency analysis (RFA) of conical implants (3.3 and 4 × 13 mm) placed in under-prepared sites on 10 and 20 pounds per cubic foot (PCF) density polyurethane sheets (simulating a D3 and D2 bone, respectively) with and without a cortical sheet of 30 PCF in density (corresponding to a D1 bone). After using ANOVA or Kolmogorov–Smirnov test to elaborate data, the resulting IT and RT values were directly proportional to the polyurethane block densities (e.g., the lowest and highest IT values were 8.36 ± 0.52 Ncm in the 10 PCF density sheet and 46.21 ± 0.79 Ncm in the 20 PCF density sheet + cortical for 4 × 13 mm implants) and increased with the increasing amount of site under-preparation (the highest results for both implants were found with a 2.2 mm under-preparation, showing a significantly higher IT with a p < 0.05 compared with others, especially in the highest-density sheets). Both implants inserted in the 20 PCF density block + cortical with all under-preparation protocols exhibited significantly higher RFA values (p < 0.05–0.0001) compared with the corresponding ones in the 10 PCF block. Moreover, 3.3 × 13 mm implants showed the same results comparing the 20 PCF block and the 10 PCF block + cortical. In conclusion, in this in vitro study using low-density polyurethane blocks, the under-preparation of the implant insertion sites was shown to be effective in increasing implants’ PS.
An Improved Feature Pyramid Network and Metric Learning Approach for Rail Surface Defect Detection
Authors: He Zhendong , Ge Shiju , He Yan , Liu Jie , An Xiaoyu
Published: May 2023

When deep learning methods are used to detect rail surface defects, the training accuracy declines due to small defects and an insufficient number of samples. This paper investigates the problem of rail surface defect detection by using an improved feature pyramid network (FPN) and the metric learning approach. Firstly, the FPN is improved by adding deformable convolution and convolutional block attention modules to improve the accuracy of detecting defects of different scales, and it is pretrained on the MS COCO dataset. Secondly, a new model is established to extract network features based on the transfer learning model and learned network parameters. Thirdly, a multimodal network structure is constructed, and the distance between each modal representative and the embedded feature vector is calculated to classify the defects. Finally, experiments are carried out on the miniImageNet dataset and the rail surface defect dataset. The results show that the mAP (five-way five-shot) of our method is 73.42% on the miniImageNet dataset and 63.29% on the rail defect dataset. Our experiments show the effectiveness of the proposed method, and the results of the rail surface defect detection are satisfactory. As there are few sample classification studies of rail surface defects, this work provides a different approach and lays a foundation for further research.
Forecasting the Distortion in Solar Radiation during Midday Hours by Analyzing Solar Radiation during Early Morning Hours
Authors: Noman Abdullah M. , Haidar Zeyad A. , Aljumah Ali S. , Almutairi Sulaiman Z. , Alqahtani Mohammed H.
Published: May 2023

Knowing the fluctuation of solar radiation is essential for reliable and safe operation of power systems with a high share of solar PV power plants. This paper introduces a novel method for forecasting the distortion in global solar radiation during the midday time (during the peak of solar radiation at which the generation of the PV plants is maximum), by analyzing the solar radiation during the very early hours. This paper shows that there is a strong relation between the condition of the solar radiation during the very early minutes of the day (when the generation of the PV plants is low) and the condition of the solar radiation during the midday hours (when the output of the PV plants is enormous). This relation can be utilized to help power systems operators in determining the safe share of PV plants that can be fed to power systems. We analyzed real data of one complete year for two sites in Saudi Arabia to approve this approach. The difference between each two readings was calculated for the hours 7 a.m. and 8 a.m. Then, the negative, zero, and amplitude of the difference was used to formulate a distortion index (DI) that predicts the distortion/fluctuation in the global radiation. It was concluded that the DI could classify the days into three categories: clean, distorted, and medium level according to the value of the DI. The accuracy of this approach was 85.2% and the error was 14.8%.
Graded Evaluation of Health Status of Hydraulic System with Variable Operating Conditions Based on Parameter Identification
Authors: Lin Fengqin , Zhang Qingxiang , Yu Peng , Guo Jin
Published: May 2023

In industrial production, the effective and reliable performance of hydraulic systems is closely associated with product quality, personal safety, economic efficiency, etc. It is of utmost significance to perform the health status evaluation of systems. In this paper, a least-squares recursive parameter identification algorithm is proposed to realize the graded evaluation of the health status of the hydraulic system under variable operating conditions. First, a nonlinear model of the hydraulic system is established based on a mechanism analysis. Based on the system identifiable model obtained by parameter linearization, the least squares recursive algorithm is used to get the system parameters. Second, the system measurable data are graded and labeled under the same operating condition, and the variable parameter ranges under different health states are obtained by the parameter identification algorithm. Finally, under variable operating conditions, the estimates of variable parameters are compared with the range of health state parameters to complete the system health state graded evaluation. The feasibility of the proposed evaluation method is verified by MATLAB simulation software.
Strength Deterioration of Earthen Sites Loess Solidified by Calcined Ginger Nuts under Dry–Wet and Freeze–Thaw Cycles
Authors: Li Qifeng , Dang Bing , Li Dandan , Hu Xiaoying
Published: May 2023

Earthen sites are a kind of constructure with significant historical and cultural value. However, the destruction of earthen sites caused by erosion occurs frequently. The solidification of calcined ginger nuts can improve the strength of the soil so that it can be used to protect the earthen sites. However, the strength degradation of solidified soil by calcined ginger nuts after dry–wet and freeze–thaw cycles is unclear. To reveal the deterioration pattern of solidified soil strength, the effects of its dosage and cycle number on the strength of solidified soil were analyzed through shear strength, dry–wet cycle, and freeze–thaw cycle tests. The results showed that the solidified soil strength decreased first and increased with dosage increase. With the number of dry–wet cycles increasing, the strength of the plain loess decreased rapidly and gradually turned flat. The strength loss of solidified soil was small in the dry–wet process. With freeze–thaw cycle numbers increasing, the strength of the plain loess decreased first and then tended to be flat, the strength of solidified soil decreased first and then increased slightly, and the change in the strength had a clear inflection point. With the increasing dosage, freeze–thaw cycle numbers corresponding to the inflection point were significantly reduced. These results indicate that calcined ginger nuts could enhance the resistance of earthen sites loess to dry–wet and freeze–thaw cycles.
A Parametric Model of Elliptic Orbits for Annual Evolutions of Northern Hemisphere Stratospheric Polar Vortex and Their Interannual Variability
Authors: Yu Yueyue , Sun Jie , Secor Michael , Cai Ming , Luo Xinyue
Published: May 2023

The year-to-year varying annual evolutions of the stratospheric polar vortex (SPV) have an important downward impact on the weather and climate from winter to summer and thus potential implications for seasonal forecasts. This study constructs a parametric elliptic orbit model for capturing the annual evolutions of mass-weighted zonal momentum at 60° N (MU) and total air mass above the isentropic surface of 400 K (M) over the latitude band of 60–90° N from 1 July 1979 to 30 June 2021. The elliptic orbit model naturally connects two time series of a nonlinear oscillator. As a result, the observed coupling relationship between MU and M associated with SPV as well as its interannual variations can be well reconstructed by a limited number of parameters of the elliptic orbit model. The findings of this study may pave a new way for short-time climate forecasts of the annual evolutions of SPV, including its temporal evolutions over winter seasons as well as the spring and fall seasons, and timings of the sudden stratospheric warming events by constructing its elliptic orbit in advance.
Parametric Expansions of an Algebraic Variety near Its Singularities
Authors: Bruno Alexander D. , Azimov Alijon A.
Published: May 2023

Presently, there is a method based on Power Geometry that allows one to find asymptotic forms and asymptotic expansions of solutions to different kinds of non-linear equations near their singularities. The method contains three algorithms: (1) Reducing the equation to its normal form, (2) separating truncated equations, and (3) power transformations of coordinates. Here, we describe the method for the simplest case, a single algebraic equation, and apply it to an algebraic variety, as described by an algebraic equation of order 12 in three variables. The variety was considered in study of Einstein’s metrics and has several singular points and singular curves. Near some of them, we compute a local parametric expansion of the variety.
Fuzzy Differential Inequalities for Convolution Product of Ruscheweyh Derivative and Multiplier Transformation
Authors: Lupaş Alina Alb
Published: May 2023

In this paper, the author combines the geometric theory of analytic function regarding differential superordination and subordination with fuzzy theory for the convolution product of Ruscheweyh derivative and multiplier transformation. Interesting fuzzy inequalities are obtained by the author.
The Modal Logic of Aristotelian Diagrams
Authors: Frijters Stef , Demey Lorenz
Published: May 2023

In this paper, we introduce and study AD-logic, i.e., a system of (hybrid) modal logic that can be used to reason about Aristotelian diagrams. The language of AD-logic, LAD, is interpreted on a kind of birelational Kripke frames, which we call “AD-frames”. We establish a sound and strongly complete axiomatization for AD-logic, and prove that there exists a bijection between finite Aristotelian diagrams (up to Aristotelian isomorphism) and finite AD-frames (up to modal isomorphism). We then show how AD-logic can express several major insights about Aristotelian diagrams; for example, for every well-known Aristotelian family A, we exhibit a formula χA∈LAD and show that an Aristotelian diagram D belongs to the family A iff χA is validated by D (when the latter is viewed as an AD-frame). Finally, we show that AD-logic itself gives rise to new and interesting Aristotelian diagrams, and we reflect on their profoundly peculiar status.
Kinematic Differential Geometry of a Line Trajectory in Spatial Movement
Authors: Almoneef Areej A. , Abdel-Baky Rashad A.
Published: May 2023

This paper investigates the kinematic differential geometry of a line trajectory in spatial movement. Specifically, we provide a theoretical expression of inflection line congruence, which is the spatial equivalent of the inflection circle of planar kinematics. Additionally, we introduce new proofs for the Euler–Savary and Disteli formulae and thoroughly analyze their spatial equivalence.
Solvability of Iterative Classes of Nonlinear Elliptic Equations on an Exterior Domain
Authors: Wang Xiaoming , Alzabut Jehad , Khuddush Mahammad , Fečkan Michal
Published: May 2023

This work explores the possibility that iterative classes of elliptic equations have both single and coupled positive radial solutions. Our approach is based on using the well-known Guo–Krasnoselskii and Avery–Henderson fixed-point theorems in a Banach space. Furthermore, we utilize Rus’ theorem in a metric space, to prove the uniqueness of solutions for the problem. Examples are constructed for the sake of verification.
One Billion hiPSC-Cardiomyocytes: Upscaling Engineered Cardiac Tissues to Create High Cell Density Therapies for Clinical Translation in Heart Regeneration
Authors: Dwyer Kiera D. , Kant Rajeev J. , Soepriatna Arvin H. , Roser Stephanie M. , Daley Mark C. , Sabe Sharif A. , Xu Cynthia M. , Choi Bum-Rak , Sellke Frank W. , Coulombe Kareen L. K.
Published: May 2023

Despite the overwhelming use of cellularized therapeutics in cardiac regenerative engineering, approaches to biomanufacture engineered cardiac tissues (ECTs) at clinical scale remain limited. This study aims to evaluate the impact of critical biomanufacturing decisions—namely cell dose, hydrogel composition, and size-on ECT formation and function—through the lens of clinical translation. ECTs were fabricated by mixing human induced pluripotent stem-cell-derived cardiomyocytes (hiPSC-CMs) and human cardiac fibroblasts into a collagen hydrogel to engineer meso-(3 × 9 mm), macro- (8 × 12 mm), and mega-ECTs (65 × 75 mm). Meso-ECTs exhibited a hiPSC-CM dose-dependent response in structure and mechanics, with high-density ECTs displaying reduced elastic modulus, collagen organization, prestrain development, and active stress generation. Scaling up, cell-dense macro-ECTs were able to follow point stimulation pacing without arrhythmogenesis. Finally, we successfully fabricated a mega-ECT at clinical scale containing 1 billion hiPSC-CMs for implantation in a swine model of chronic myocardial ischemia to demonstrate the technical feasibility of biomanufacturing, surgical implantation, and engraftment. Through this iterative process, we define the impact of manufacturing variables on ECT formation and function as well as identify challenges that must still be overcome to successfully accelerate ECT clinical translation.
A Computer Method for Pronation-Supination Assessment in Parkinson’s Disease Based on Latent Space Representations of Biomechanical Indicators
Authors: Sánchez-Fernández Luis Pastor , Garza-Rodríguez Alejandro , Sánchez-Pérez Luis Alejandro , Martínez-Hernández Juan Manuel
Published: May 2023

One problem in the quantitative assessment of biomechanical impairments in Parkinson’s disease patients is the need for scalable and adaptable computing systems. This work presents a computational method that can be used for motor evaluations of pronation-supination hand movements, as described in item 3.6 of the Unified Parkinson’s Disease Rating Scale (MDS-UPDRS). The presented method can quickly adapt to new expert knowledge and includes new features that use a self-supervised training approach. The work uses wearable sensors for biomechanical measurements. We tested a machine-learning model on a dataset of 228 records with 20 indicators from 57 PD patients and eight healthy control subjects.. The test dataset's experimental results show that the method's precision rates for the pronation and supination classifi-cation task achieved up to 89% accuracy, and the F1-scores were higher than 88% in most categories. The scores present a root mean squared error of 0.28 when compared to expert clinician scores. The paper provides detailed results for pronation-supination hand movement evaluations using a new analysis method when compared to the other methods mentioned in the literature. Furthermore, the proposal consists of a scalable and adaptable model that includes expert knowledge and affectations not covered in the MDS-UPDRS for a more in-depth evaluation.
Could the Convergence of Science and Technology Guarantee Human Health in the Future?
Authors: Zarrabi Ali
Published: May 2023

Due to the daily growth of the world population, there has been an increase in concerns regarding health, especially due to the increase in the number of aged people, the surge of pollution, and the appearance of new pandemic diseases such as COVID-19 and influenza H1N1 [...]
CT Imaging of Eustachian Tube Balloon Dilation: Method Development on Cadaver Heads
Authors: Cetin-Ferra Selma , Teixeira Miriam S. , Swarts J. Douglas , Rath Tanya J. , Alper Cuneyt M.
Published: May 2023

Objective: To develop a methodology for the measurement of balloon dilation (BD) effects on Eustachian Tube (ET) structure using Computerized Tomography (CT) images. Methods: The BD of the ET was performed on three cadaver heads (five ears) through the nasopharyngeal orifice. The axial CT images of the temporal bones were obtained before dilation, while an inflated balloon was in the lumen of ET, and after balloon removal in each ear. Utilizing Dicom images captured by the ImageJ software 3D volume viewer function, the anatomical landmark coordinates of the ET were matched with their pre- and post-dilation counterparts, and the longitudinal axis of the ET was captured with serial images. The histograms of the regions of interest (ROI) and three different lumen width and length measurements were obtained from captured images. The densities of air, tissue, and bone were determined with histograms as a baseline to determine the BD rate as a function of increased air in the lumen. Results: The small ROI box included the area of prominently dilated ET lumen after BD and best represented the visually obvious changes in the lumen, compared to the ROIs that extended the wider areas (longest and longer). Air density was the outcome measure for comparison with each corresponding baseline value. The average increase in air density in the small ROI was 64%, while the longest and long ROI boxes showed 44 and 56% increases, respectively. Conclusion: This study describes a method to image the ET and quantify the outcomes of BD of the ET using anatomical landmarks.
Biotests in Cyanobacterial Toxicity Assessment—Efficient Enough or Not?
Authors: Davidović Petar , Blagojević Dajana , Meriluoto Jussi , Simeunović Jelica , Svirčev Zorica
Published: May 2023

Cyanobacteria are a diverse group of organisms known for producing highly potent cyanotoxins that pose a threat to human, animal, and environmental health. These toxins have varying chemical structures and toxicity mechanisms and several toxin classes can be present simultaneously, making it difficult to assess their toxic effects using physico-chemical methods, even when the producing organism and its abundance are identified. To address these challenges, alternative organisms among aquatic vertebrates and invertebrates are being explored as more assays evolve and diverge from the initially established and routinely used mouse bioassay. However, detecting cyanotoxins in complex environmental samples and characterizing their toxic modes of action remain major challenges. This review provides a systematic overview of the use of some of these alternative models and their responses to harmful cyanobacterial metabolites. It also assesses the general usefulness, sensitivity, and efficiency of these models in investigating the mechanisms of cyanotoxicity expressed at different levels of biological organization. From the reported findings, it is clear that cyanotoxin testing requires a multi-level approach. While studying changes at the whole-organism level is essential, as the complexities of whole organisms are still beyond the reach of in vitro methodologies, understanding cyanotoxicity at the molecular and biochemical levels is necessary for meaningful toxicity evaluations. Further research is needed to refine and optimize bioassays for cyanotoxicity testing, which includes developing standardized protocols and identifying novel model organisms for improved understanding of the mechanisms with fewer ethical concerns. In vitro models and computational modeling can complement vertebrate bioassays and reduce animal use, leading to better risk assessment and characterization of cyanotoxins.
Agouti-Signalling Protein Overexpression Reduces Aggressiveness in Zebrafish
Authors: Rocha Ana , Godino-Gimeno Alejandra , Rotllant Josep , Cerdá-Reverter José Miguel
Published: May 2023

Feeding motivation plays a crucial role in food intake and growth. It closely depends on hunger and satiation, which are controlled by the melanocortin system. Overexpression of the inverse agonist agouti-signalling protein (ASIP) and agouti-related protein (AGRP) leads to enhanced food intake, linear growth, and weight. In zebrafish, overexpression of Agrp leads to the development of obesity, in contrast to the phenotype observed in transgenic zebrafish that overexpress asip1 under the control of a constitutive promoter (asip1-Tg). Previous studies have demonstrated that asip1-Tg zebrafish exhibit larger sizes but do not become obese. These fish display increased feeding motivation, resulting in a higher feeding rate, yet a higher food ration is not essential in order to grow larger than wild-type (WT) fish. This is most likely attributed to their improved intestinal permeability to amino acids and enhanced locomotor activity. A relationship between high feeding motivation and aggression has been previously reported in some other transgenic species showing enhanced growth. This study aims to elucidate whether the hunger observed in asip1-Tg is linked to aggressive behaviour. Dominance and aggressiveness were quantified using dyadic fights and mirror-stimulus tests, in addition to the analysis of basal cortisol levels. The results indicate that asip1-Tg are less aggressive than WT zebrafish in both dyadic fights and mirror-stimulus tests.
Dopamine D1 Agonists: First Potential Treatment for Late-Stage Parkinson’s Disease
Authors: Lewis Mechelle M. , Van Scoy Lauren J. , De Jesus Sol , Hakun Jonathan G. , Eslinger Paul J. , Fernandez-Mendoza Julio , Kong Lan , Yang Yang , Snyder Bethany L. , Loktionova Natalia , Duvvuri Sridhar , Gray David L. , Huang Xuemei , Mailman Richard B.
Published: May 2023

Current pharmacotherapy has limited efficacy and/or intolerable side effects in late-stage Parkinson’s disease (LsPD) patients whose daily life depends primarily on caregivers and palliative care. Clinical metrics inadequately gauge efficacy in LsPD patients. We explored if a D1/5 dopamine agonist would have efficacy in LsPD using a double-blind placebo-controlled crossover phase Ia/b study comparing the D1/5 agonist PF-06412562 to levodopa/carbidopa in six LsPD patients. Caregiver assessment was the primary efficacy measure because caregivers were with patients throughout the study, and standard clinical metrics inadequately gauge efficacy in LsPD. Assessments included standard quantitative scales of motor function (MDS-UPDRS-III), alertness (Glasgow Coma and Stanford Sleepiness Scales), and cognition (Severe Impairment and Frontal Assessment Batteries) at baseline (Day 1) and thrice daily during drug testing (Days 2–3). Clinicians and caregivers completed the clinical impression of change questionnaires, and caregivers participated in a qualitative exit interview. Blinded triangulation of quantitative and qualitative data was used to integrate findings. Neither traditional scales nor clinician impression of change detected consistent differences between treatments in the five participants who completed the study. Conversely, the overall caregiver data strongly favored PF-06412562 over levodopa in four of five patients. The most meaningful improvements converged on motor, alertness, and functional engagement. These data suggest for the first time that there can be useful pharmacological intervention in LsPD patients using D1/5 agonists and also that caregiver perspectives with mixed method analyses may overcome limitations using methods common in early-stage patients. The results encourage future clinical studies and understanding of the most efficacious signaling properties of a D1 agonist for this population.
Microvascular Contributions to Alzheimer Disease Pathogenesis: Is Alzheimer Disease Primarily an Endotheliopathy?
Authors: Tarawneh Rawan
Published: May 2023

Alzheimer disease (AD) models are based on the notion that abnormal protein aggregation is the primary event in AD, which begins a decade or longer prior to symptom onset, and culminates in neurodegeneration; however, emerging evidence from animal and clinical studies suggests that reduced blood flow due to capillary loss and endothelial dysfunction are early and primary events in AD pathogenesis, which may precede amyloid and tau aggregation, and contribute to neuronal and synaptic injury via direct and indirect mechanisms. Recent data from clinical studies suggests that endothelial dysfunction is closely associated with cognitive outcomes in AD and that therapeutic strategies which promote endothelial repair in early AD may offer a potential opportunity to prevent or slow disease progression. This review examines evidence from clinical, imaging, neuropathological, and animal studies supporting vascular contributions to the onset and progression of AD pathology. Together, these observations support the notion that the onset of AD may be primarily influenced by vascular, rather than neurodegenerative, mechanisms and emphasize the importance of further investigations into the vascular hypothesis of AD.
Socio-Demographic, Lifestyle, and Cardiometabolic Characteristics Associated with Low-Grade Systemic Inflammation in Russian Adult Population
Authors: Mirolyubova Olga , Kholmatova Kamila , Postoeva Anna , Kostrova Galina , Malyutina Sofia , Kudryavtsev Alexander V.
Published: May 2023

Mortality from cardiovascular diseases (CVDs) is higher in Russia compared to other European countries. High-sensitivity C-reactive protein (hs-CRP) is a biomarker of inflammation, and its elevated levels indicate increased CVD risks. We aim to describe the prevalence of low-grade systemic inflammation (LGSI) and the associated factors in a Russian population. The Know Your Heart cross-sectional study was conducted in Arkhangelsk, Russia in 2015–2017 with a population sample aged 35–69 years (n = 2380). LGSI was defined as hs-CRP ≥ 2 and < 10 mg/L, and its associations with socio-demographic, lifestyle, and cardiometabolic characteristics were analyzed. The prevalence of LGSI (age-standardized to European Standard Population 2013) was 34.1% (33.5% in men and 36.1% in women). In the total sample, the increased odds ratios (ORs) of LGSI were associated with abdominal obesity (2.1), smoking (1.9), dyslipidemia (1.5), pulmonary diseases (1.4), and hypertension (1.3); the decreased ORs were in women (0.6) and in married participants (0.6). In men, the ORs were higher with abdominal obesity (2.1), smoking (2.0), CVDs (1.5), and hazardous drinking (1.5); in women—with abdominal obesity (4.4) and pulmonary diseases (1.5). In conclusion, one-third of the adult population in Arkhangelsk had LGSI. Abdominal obesity was the strongest LGSI correlate in both sexes, while the profiles of other associated factors were different between men and women.
Research Progress in Calcitonin Gene-Related Peptide and Bone Repair
Authors: Wang Qichang , Qin Haotian , Deng Jiapeng , Xu Huihui , Liu Su , Weng Jian , Zeng Hui
Published: May 2023

Calcitonin gene-related peptide (CGRP) has 37 amino acids. Initially, CGRP had vasodilatory and nociceptive effects. As research progressed, evidence revealed that the peripheral nervous system is closely associated with bone metabolism, osteogenesis, and bone remodeling. Thus, CGRP is the bridge between the nervous system and the skeletal muscle system. CGRP can promote osteogenesis, inhibit bone resorption, promote vascular growth, and regulate the immune microenvironment. The G protein-coupled pathway is vital for its effects, while MAPK, Hippo, NF-κB, and other pathways have signal crosstalk, affecting cell proliferation and differentiation. The current review provides a detailed description of the bone repair effects of CGRP, subjected to several therapeutic studies, such as drug injection, gene editing, and novel bone repair materials.
A Dysferlin Exon 32 Nonsense Mutant Mouse Model Shows Pathological Signs of Dysferlinopathy
Authors: Ballouhey Océane , Chapoton Marie , Alary Benedicte , Courrier Sébastien , Da Silva Nathalie Da , Krahn Martin , Lévy Nicolas , Weisleder Noah , Bartoli Marc
Published: May 2023

Dysferlinopathies are a group of autosomal recessive muscular dystrophies caused by pathogenic variants in the DYSF gene. While several animal models of dysferlinopathy have been developed, most of them involve major disruptions of the Dysf gene locus that are not optimal for studying human dysferlinopathy, which is often caused by single nucleotide substitutions. In this study, the authors describe a new murine model of dysferlinopathy that carries a nonsense mutation in Dysf exon 32, which has been identified in several patients with dysferlinopathy. This mouse model, called Dysf p.Y1159X/p.Y1159X, displays several molecular, histological, and functional defects observed in dysferlinopathy patients and other published mouse models. This mutant mouse model is expected to be useful for testing various therapeutic approaches such as termination codon readthrough, pharmacological approaches, and exon skipping. Therefore, the data presented in this study strongly support the use of this animal model for the development of preclinical strategies for the treatment of dysferlinopathies.
The Imitation of the Ovarian Fatty Acid Profile of Superfertile Dummerstorf Mouse Lines during IVM of Control Line Oocytes Could Influence Their Maturation Rates
Authors: Calanni-Pileri Michela , Michaelis Marten , Langhammer Martina , Tognetti Paolo Rosellini , Weitzel Joachim M.
Published: May 2023

Declining human fertility worldwide is an attractive research target for the search for “high fertility” genes and pathways to counteract this problem. To study these genes and pathways for high fertility, the superfertile Dummerstorf mouse lines FL1 and FL2 are two unique model organisms representing an improved fertility phenotype. A direct reason for this remarkable characteristic of increased litter size, which reaches >20 pups/litter in both FLs, is the raised ovulation rate by approximately 100%, representing an impressive record in this field. Dummerstorf high-fertility lines incarnate extraordinary and singular models of high-fertility for other species, mostly farm animals, with the aim of improving production and reducing costs. Our main goal is to describe the genetic and molecular pathways to reach their phenotypical excellence, and to reproduce them using the control population. The large litter size and ovulation rate in Dummerstorf lines are mostly due to an increase in the quality of their oocytes, which receive a different intake of fat and are composed of different types and concentrations of fatty acids. As the follicular microenvironment plays a fundamental role during the oocytes development, in the present manuscript, we tried to improve the in vitro maturation technique by mimicking the fatty acid profile of FLs oocytes during the IVM of control oocytes. Currently, the optimization of the IVM system is fundamental mostly for prepubertal girls and oncological patients whose main source of gametes to restore fertility may be their maturation in vitro. Our data suggest that the specific fatty acid composition of FLs COCs can contribute to their high-fertility phenotype. Indeed, COCs from the control line matured in IVM-medium supplemented with C14:0 (high in FL2 COCs) or with C20:0, C21:0, C22:0, and C23:0 (high in FL1 COCs), but also control oocytes without cumulus, whose concentration in long-chain FAs are “naturally” higher, showing a slightly higher maturation rate. These findings represent an important starting point for the optimization of the IVM system using FA supplementation.
Immunomodulatory Role of Vitamin D on Gut Microbiome in Children
Authors: Tabassum Anika , Ali Adli , Zahedi Farah Dayana , Ismail Noor Akmal Shareela
Published: May 2023

Vitamin D plays a role in regulating the immune system and can be linked to the alteration of the gut microbiome, which leads to several immunological diseases. This systematic review aims to explore the relationship between Vitamin D and children’s gut microbiome, as well as its impact towards the immune system. We have systematically collated relevant studies from different databases concerning changes in the gut microbiome of children from infants to 18 years old associated with Vitamin D and the immunological pathways. The studies utilized 16S rRNA sequencing analysis of fecal matter with or without Vitamin D supplementation and Vitamin D levels. Ten studies were selected for the review, among which eight studies showed significant alterations in the gut microbiome related to Vitamin D supplementation or Vitamin D levels. The taxa of the phylum Actinobacteria, Bacteroidetes, Firmicutes, and Proteobacteria are the most altered in these studies. The alteration of the taxa alters the Th1 and Th2 pathways and changes the immune response. We will discuss how Vitamin D may contribute to the activation of immune pathways via its effects on intestinal barrier function, microbiome composition, and/or direct effects on immune responses. In conclusion, the studies examined in this review have provided evidence that Vitamin D levels may have an impact on the composition of children’s gut microbiomes.