bluuebunny/crossref_metadata_2025 huggingface dataset:
TransPhoM-DS Study Grant Report: Rationale and Protocol for Investigating the Efficacy of Low-Power Transcranial Photobiomodulation on Language, Executive Function, Attention, and Memory in Down Syndrome
Authors: Vieira Willians Fernando , Coelho David Richer Araujo , Gersten Maia , Puerto Aura Maria Hurtado , Kalli Stefani , Gonzalez-Garibay Guillermo , McEachern Kayla , Clancy Julie A. , Skotko Brian G. , Abbeduto Leonard , Thurman Angela John , Pulsifer Margaret B. , Corcoran Elizabeth , Saltmarche Anita E. , Naeser Margaret A. , Cassano Paolo
Published: July 2024

Down syndrome (DS) is the leading genetic cause of intellectual disability globally, affecting about 1 in every 800 births. Individuals with DS often face various neuropsychiatric conditions alongside intellectual disabilities due to altered brain development. Despite the diverse phenotypic expressions of DS, typical physical characteristics frequently influence language development and acquisition. EEG studies have identified abnormal oscillatory patterns in individuals with DS. Emerging interventions targeting the enhancement of gamma (40 Hz) neuronal oscillations show potential for improving brain electrical activity and cognitive functions in this population. However, effective cognitive interventions for DS remain scarce. Extensive research indicates that transcranial photobiomodulation (t-PBM) with near-infrared (NIR) light can penetrate deeply into the cerebral cortex, modulate cortical excitability, and enhance cerebral perfusion and oxygenation. Furthermore, t-PBM has been shown to improve cognitive functions such as language, attention, inhibition, learning, and memory, including working memory. This study presents the rationale and design of an ongoing randomized, sham-controlled clinical trial aimed at assessing the effectiveness of t-PBM using NIR light in enhancing the language abilities of individuals with DS.
Improved Res-UNet Network for Phase Unwrapping of Interferometric Gear Tooth Flank Measurements
Authors: Wang Xian , Ju Chaoyang , Xuan Yufan , Shi Ting , Yang Feiqi , Liu Yun , Kou Ke , Zhao Yichao
Published: July 2024

This article introduces an improved deep learning network, GRU-Net, designed to facilitate direct and precise phase unwrapping of wrapped phase measurements in gear tooth surface interferometry. GRU-Net incorporates a Gram matrix within each down-sampling process to compute style loss, thereby capturing essential stripe structure information features. This network exhibits enhanced capability in handling larger and more intricate gear tooth interferograms, particularly in scenarios involving pronounced noise and aliasing, while still yielding favorable outcomes. A comparative evaluation was conducted, contrasting GRU-Net with the Res-UNet network and other conventional methods. The results demonstrate that GRU-Net surpasses the alternative approaches in terms of unwrapping accuracy, noise resilience, and anti-aliasing capabilities, with accuracy improved by at least 24%, exhibiting significantly superior performance. Additionally, in contrast to the Res-UNet network, GRU-Net demonstrates accelerated learning speed and generates more compact models.
Cloning, Expression and Enzymatic Characterization of Pectin Methyl Esterase from Populus trichocarpa and Its Application
Authors: Feng Yanjiao , Huang Lifen , Zeng Yue , Zhang Yiyuan , Liu Wei , He Gang
Published: July 2024

The pectin methyl esterase gene from Populus trichocarpa (PtPME) was successfully cloned through PCR amplification and subsequently inserted into the expressing vector pMAL-c5e for successful expression in Escherichia coli BL21 (DE3). Initially, we determined the primary enzymatic properties of PtPME, a pectin methyl esterase derived from Populus trichocarpa. Notably, this enzyme exhibits a higher affinity towards citrus pectin, with an esterification degree exceeding 60%. Furthermore, this enzyme’s optimal reaction temperature and pH were found to be 30 °C and 8, respectively. Importantly, its exceptional stability under neutral conditions highlights its potential application in the industrial production of low-ester pectin.
The Micropore Characteristics and Geological Significance of a Tuffaceous Tight Reservoir Formed by Burial Dissolution: A Case Study of the Carboniferous Tuff in the Santanghu Basin, NW China
Authors: Ma Jian , Pan Yongshuai , Tong Zhongzheng , Zhang Guoqiang
Published: July 2024

As a distinct type of reservoir, tuffaceous tight reservoirs have attracted much attention. However, previous studies on tuffaceous tight reservoirs formed in the burial diagenetic stage are few, particularly regarding the genesis of micropores, which restricts the in-depth exploration of tuffaceous tight oil. According to thin section observation, scanning electron microscopy (SEM) identification, X-ray diffraction (XRD) experiments, elemental analyses, porosity and permeability tests, and pore structure analyses, the micropore characteristics of the Carboniferous tuffaceous tight reservoir formed by burial dissolution in the Santanghu Basin, NW China, are studied. In addition, the cause of the tuff micropore formation and its geological significance are also researched in this paper. The results are as follows: (1) The tuffaceous tight reservoir formed by burial dissolution mainly consists of quartz, feldspar, dolomite, and clay minerals. The reservoir space mainly consists of intergranular pores between minerals, intragranular dissolution pores within feldspars, calcite, dolomite, clay minerals, and locally developed organic matter pores. (2) The formation of micropores in tuff reservoirs formed by burial dissolution is mainly related to the original composition of the tuff. (3) Tuffaceous reservoirs with good physical properties are usually formed at the bottom or top of a large set of source rock. The results of this investigation can provide innovative theoretical evidence for the accumulation mechanism of tuffaceous tight oil formed by burial dissolution. Meanwhile, it can be considered a reference regarding the distribution of and predictions for tuffaceous reservoirs formed by burial dissolution in similar situations in other parts of the world.
Establishment of a Mass Concrete Strength-Monitoring Method Using Barium Titanate–Bismuth Ferrite/Polyvinylidene Fluoride Nanocomposite Piezoelectric Sensors with Temperature Stability
Authors: Lin Guoliang , Lu Dongwang , Cui Bowen , Lin Aoxiang , Liu Minyi , Ye Yongbin
Published: July 2024

Mass concrete is widely used in large-scale projects, including metro upper cover structures, water conservancy dams, and heavy equipment foundations, among others, necessitating the process of health monitoring in mass concrete construction. The development of reliable and simple strength-monitoring methods for mass concrete is challenging because the inner temperature of mass concrete is high and changes a lot. This study proposes a strength-monitoring approach for mass concrete using barium titanate–bismuth ferrite/polyvinylidene fluoride (BT–BFO/PVDF) nanocomposite piezoelectric sensors, wherein the new sensors are embedded as actuators and sensors in mass concrete. The stress wave generated by the BT–BFO/PVDF piezoelectric sensors is used to monitor the specimen’s strength for 28 days. The piezoelectric voltage received by the sensors in mass concrete is analyzed. The experimental results indicate that the signal received by the BT–BFO/PVDF sensors is not easily affected by the internal temperature of mass concrete compared with that of the traditional PVDF piezoelectric sensors. The signal parameters sensitive to concrete strength variation and the change trend of concrete strength are closely related to the piezoelectric voltage. Therefore, the proposed approach using BT–BFO/PVDF nanocomposite piezoelectric sensors is efficient (error < 10%) in mass concrete monitoring. Moreover, the monitoring results do not need temperature compensation. The physical meaning of the obtained strength prediction formula is proposed. An experimental system based on PVDF dynamic strain-sensing characteristics is established.
A Review on the Video-Based River Discharge Measurement Technique
Authors: Chen Meng , Chen Hua , Wu Zeheng , Huang Yu , Zhou Nie , Xu Chong-Yu
Published: July 2024

The hydrological monitoring of flow data is important for flood prevention and modern river management. However, traditional contact methods are increasingly struggling to meet the requirements of simplicity, accuracy, and continuity. The video-based river discharge measurement is a technique to monitor flow velocity without contacting the water body by using the image-recognition algorithms, which has been verified to have the advantages of full coverage and full automation compared with the traditional contact technique. In order to provide a timely summary of the available results and to inform further research and applications, this paper reviews and synthesizes the literature on the general implementation routes of the video-based river discharge measurement technique and the principles and advances of today’s popular image-recognition algorithms for velocity detection. Then, it discusses the challenges of image-recognition algorithms in terms of image acquisition conditions, parameter uncertainties, and complex meteorological and water environments. It is concluded that the performance of this technique can be improved by enhancing the robustness and accuracy of video-based discharge measurement algorithms, minimizing weather effects, and improving computational efficiency. Finally, future development directions for further perfecting this technique are outlined.
Physical Functioning, Physical Activity, and Variability in Gait Performance during the Six-Minute Walk Test
Authors: Rekant Julie , Ortmeyer Heidi , Giffuni Jamie , Friedman Ben , Addison Odessa
Published: July 2024

Instrumenting the six-minute walk test (6MWT) adds information about gait quality and insight into fall risk. Being physically active and preserving multi-directional stepping abilities are also important for fall risk reduction. This analysis investigated the relationship of gait quality during the 6MWT with physical functioning and physical activity. Twenty-one veterans (62.2 ± 6.4 years) completed the four square step test (FSST) multi-directional stepping assessment, a gait speed assessment, health questionnaires, and the accelerometer-instrumented 6MWT. An activity monitor worn at home captured free-living physical activity. Gait measures were not significantly different between minutes of the 6MWT. However, participants with greater increases in stride time (ρ = −0.594, p < 0.01) and stance time (ρ = −0.679, p < 0.01) during the 6MWT reported lower physical functioning. Neither physical activity nor sedentary time were related to 6MWT gait quality. Participants exploring a larger range in stride time variability (ρ = 0.614, p < 0.01) and stance time variability (ρ = 0.498, p < 0.05) during the 6MWT required more time to complete the FSST. Participants needing at least 15 s to complete the FSST meaningfully differed from those completing the FSST more quickly on all gait measures studied. Instrumenting the 6MWT helps detect ranges of gait performance and provides insight into functional limitations missed with uninstrumented administration. Established FSST cut points identify aging adults with poorer gait quality.
Inkjet Printing Magnetostrictive Materials for Structural Health Monitoring of Carbon Fibre-Reinforced Polymer Composite
Authors: Ahmed Nisar , Smith Patrick J. , Morley Nicola A.
Published: July 2024

Inkjet printing of magnetic materials has increased in recent years, as it has the potential to improve research in smart, functional materials. Magnetostriction is an inherent property of magnetic materials which allows strain or magnetic fields to be detected. This makes it very attractive for sensors in the area of structural health monitoring by detecting internal strains in carbon fibre-reinforced polymer (CFRP) composite. Inkjet printing offers design flexibility for these sensors to influence the magnetic response to the strain. This allows the sensor to be tailored to suit the location of defects in the CFRP. This research has looked into the viability of printable soft magnetic materials for structural health monitoring (SHM) of CFRP. Magnetite and nickel ink dispersions were selected to print using the JetLab 4 drop-on-demand technique. The printability of both inks was tested by selecting substrate, viscosity and solvent evaporation. Clogging was found to be an issue for both ink dispersions. Sonicating and adjusting the jetting parameters helped in distributing the nanoparticles. We found that magnetite nanoparticles were ideal as a sensor as there is more than double increase in saturation magnetisation by 49 Am2/kg and more than quadruple reduction of coercive field of 5.34 kA/m than nickel. The coil design was found to be the most sensitive to the field as a function of strain, where the gradient was around 80% higher than other sensor designs. Additive layering of 10, 20 and 30 layers of a magnetite square patch was investigated, and it was found that the 20-layered magnetite print had an improved field response to strain while maintaining excellent print resolution. SHM of CFRP was performed by inducing a strain via bending and it was found that the magnetite coil detected a change in field as the strain was applied.
Deep Learning Soft-Decision GNSS Multipath Detection and Mitigation
Authors: Nunes Fernando , Sousa Fernando
Published: July 2024

A technique is proposed to detect the presence of the multipath effect in Global Navigation Satellite Signal (GNSS) signals using a convolutional neural network (CNN) as the building block. The network is trained and validated, for a wide range of C/N0 values, with a realistic dataset constituted by the synthetic noisy outputs of a 2D grid of correlators associated with different Doppler frequencies and code delays (time-domain dataset). Multipath-disturbed signals are generated in agreement with the various scenarios encompassed by the adopted multipath model. It was found that pre-processing the outputs of the correlators grid with the two-dimensional Discrete Fourier Transform (frequency-domain dataset) enables the CNN to improve the accuracy relative to the time-domain dataset. Depending on the kind of CNN outputs, two strategies can then be devised to solve the equation of navigation: either remove the disturbed signal from the equation (hard decision) or process the pseudoranges with a weighted least-squares algorithm, where the entries of the weighting matrix are computed using the analog outputs of the neural network (soft decision).
Flexible Sensors Based on Conductive Polymer Composites
Authors: Zhao Dan , Jia Weiwei , Feng Xiaona , Yang Huali , Xie Yali , Shang Jie , Wang Pengjun , Guo Yufeng , Li Run-Wei
Published: July 2024

Elastic polymer-based conductive composites (EPCCs) are of great potential in the field of flexible sensors due to the advantages of designable functionality and thermal and chemical stability. As one of the popular choices for sensor electrodes and sensitive materials, considerable progress in EPCCs used in sensors has been made in recent years. In this review, we introduce the types and the conductive mechanisms of EPCCs. Furthermore, the recent advances in the application of EPCCs to sensors are also summarized. This review will provide guidance for the design and optimization of EPCCs and offer more possibilities for the development and application of flexible sensors.
EcoDetect-YOLO: A Lightweight, High-Generalization Methodology for Real-Time Detection of Domestic Waste Exposure in Intricate Environmental Landscapes
Authors: Liu Shenlin , Chen Ruihan , Ye Minhua , Luo Jiawei , Yang Derong , Dai Ming
Published: July 2024

In response to the challenges of accurate identification and localization of garbage in intricate urban street environments, this paper proposes EcoDetect-YOLO, a garbage exposure detection algorithm based on the YOLOv5s framework, utilizing an intricate environment waste exposure detection dataset constructed in this study. Initially, a convolutional block attention module (CBAM) is integrated between the second level of the feature pyramid etwork (P2) and the third level of the feature pyramid network (P3) layers to optimize the extraction of relevant garbage features while mitigating background noise. Subsequently, a P2 small-target detection head enhances the model’s efficacy in identifying small garbage targets. Lastly, a bidirectional feature pyramid network (BiFPN) is introduced to strengthen the model’s capability for deep feature fusion. Experimental results demonstrate EcoDetect-YOLO’s adaptability to urban environments and its superior small-target detection capabilities, effectively recognizing nine types of garbage, such as paper and plastic trash. Compared to the baseline YOLOv5s model, EcoDetect-YOLO achieved a 4.7% increase in mAP0.5, reaching 58.1%, with a compact model size of 15.7 MB and an FPS of 39.36. Notably, even in the presence of strong noise, the model maintained a mAP0.5 exceeding 50%, underscoring its robustness. In summary, EcoDetect-YOLO, as proposed in this paper, boasts high precision, efficiency, and compactness, rendering it suitable for deployment on mobile devices for real-time detection and management of urban garbage exposure, thereby advancing urban automation governance and digital economic development.
LiDAR-Based 3D Temporal Object Detection via Motion-Aware LiDAR Feature Fusion
Authors: Park Gyuhee , Koh Junho , Kim Jisong , Moon Jun , Choi Jun Won
Published: July 2024

Recently, the growing demand for autonomous driving in the industry has led to a lot of interest in 3D object detection, resulting in many excellent 3D object detection algorithms. However, most 3D object detectors focus only on a single set of LiDAR points, ignoring their potential ability to improve performance by leveraging the information provided by the consecutive set of LIDAR points. In this paper, we propose a novel 3D object detection method called temporal motion-aware 3D object detection (TM3DOD), which utilizes temporal LiDAR data. In the proposed TM3DOD method, we aggregate LiDAR voxels over time and the current BEV features by generating motion features using consecutive BEV feature maps. First, we present the temporal voxel encoder (TVE), which generates voxel representations by capturing the temporal relationships among the point sets within a voxel. Next, we design a motion-aware feature aggregation network (MFANet), which aims to enhance the current BEV feature representation by quantifying the temporal variation between two consecutive BEV feature maps. By analyzing the differences and changes in the BEV feature maps over time, MFANet captures motion information and integrates it into the current feature representation, enabling more robust and accurate detection of 3D objects. Experimental evaluations on the nuScenes benchmark dataset demonstrate that the proposed TM3DOD method achieved significant improvements in 3D detection performance compared with the baseline methods. Additionally, our method achieved comparable performance to state-of-the-art approaches.
Role of Graphene in Surface Plasmon Resonance-Based Biosensors
Authors: Tene Talia , Bellucci Stefano , Arias Arias Fabian , Carrera Almendariz Luis Santiago , Flores Huilcapi Ana Gabriela , Vacacela Gomez Cristian
Published: July 2024

This work explores the transformative role of graphene in enhancing the performance of surface plasmon resonance (SPR)-based biosensors. The motivation for this review stems from the growing interest in the unique properties of graphene, such as high surface area, excellent electrical conductivity, and versatile functionalization capabilities, which offer significant potential to improve the sensitivity, specificity, and stability of SPR biosensors. This review systematically analyzes studies published between 2010 and 2023, covering key metrics of biosensor performance. The findings reveal that the integration of graphene consistently enhances sensitivity. Specificity, although less frequently reported numerically, showed promising results, with high specificity achieved at sub-nanomolar concentrations. Stability enhancements are also significant, attributed to the protective properties of graphene and improved biomolecule adsorption. Future research should focus on mechanistic insights, optimization of integration techniques, practical application testing, scalable fabrication methods, and comprehensive comparative studies. Our findings provide a foundation for future research, aiming to further optimize and harness the unique physical properties of graphene to meet the demands of sensitive, specific, stable, and rapid biosensing in various practical applications.
Scalp Electroencephalogram-Derived Involvement Indexes during a Working Memory Task Performed by Patients with Epilepsy
Authors: Iammarino Erica , Marcantoni Ilaria , Sbrollini Agnese , Mortada MHD Jafar , Morettini Micaela , Burattini Laura
Published: July 2024

Electroencephalography (EEG) wearable devices are particularly suitable for monitoring a subject’s engagement while performing daily cognitive tasks. EEG information provided by wearable devices varies with the location of the electrodes, the suitable location of which can be obtained using standard multi-channel EEG recorders. Cognitive engagement can be assessed during working memory (WM) tasks, testing the mental ability to process information over a short period of time. WM could be impaired in patients with epilepsy. This study aims to evaluate the cognitive engagement of nine patients with epilepsy, coming from a public dataset by Boran et al., during a verbal WM task and to identify the most suitable location of the electrodes for this purpose. Cognitive engagement was evaluated by computing 37 engagement indexes based on the ratio of two or more EEG rhythms assessed by their spectral power. Results show that involvement index trends follow changes in cognitive engagement elicited by the WM task, and, overall, most changes appear most pronounced in the frontal regions, as observed in healthy subjects. Therefore, involvement indexes can reflect cognitive status changes, and frontal regions seem to be the ones to focus on when designing a wearable mental involvement monitoring EEG system, both in physiological and epileptic conditions.
Negotiating Visibility: Mediating Presence through Zoom Camera Choices in Post-Secondary Students during COVID-19
Authors: Cupchik Gerald C. , Rebello Clara B. , Albar Renad , Cocunato Jessica , Cupchik Eva , Ignacio Angelie , Faubert Emily
Published: July 2024

Students at a large and socially diverse urban university completed an anonymous survey examining online learning experiences during the COVID-19 pandemic with an emphasis on decisions to keep their cameras on or off during synchronous class. The 505 student respondents used 7-point scales to assess their school performance and everyday life experiences during the pandemic, general classroom values, pre-pandemic and current pandemic experiences, technological proficiencies related to Zoom, and camera on/off attitudes, as well as the online behavior of professors, and the role of social media in their everyday lives. The findings underscored two motivations underlying school engagement. Students could be motivated by a need for belonging involving authentic self-presentation while experiencing the emotional presence of others, and/or be instrumentally motivated by a need to perform well and advance their careers. The importance of professors creating a safe online space to foster a sense of belonging was highlighted. Finally, the findings show that feelings about having one’s camera on or off during online classes are related to everyday social media experiences. The social-emotional and pragmatic aspects of university education are complementary facets of a university experience.
Drivers and Barriers towards Circular Economy in Rural Tourism Destinations: A Case Study of Tunis Village, Egypt
Authors: Alharethi Thaib , Abdelhakim Ayman , Mohammed Ahmad
Published: July 2024

This study explores the drivers and barriers of the Circular Economy (CE) in Tunis Village, a rural tourism destination, as a case study of emerging economics. We adopted an exploratory case study methodology. Telephone interviews (n = 10) with stakeholders were conducted, and a survey of employees (n = 123) was distributed. Qualitative data were thematically analyzed, and quantitative data were descriptively presented. The results show that improving relationships with the local community, gaining financial benefits, and improving relationships with suppliers were the top perceived drivers. The top perceived barriers are poor economic development, which makes the implementation of large-scale sustainability difficult; a lack of technology and advanced technologies; and the absence of effective and integrated waste management and recycling systems. Considering the exploratory nature and design of this study, the results cannot be generalized. However, the results can help plan future research on a larger scale in developing economies. Furthermore, the findings can inform policymakers on how to better apply CE practices in rural tourism destinations. The topic of CE has been under-researched in connection with developed countries, and this study is the first to examine CE in rural tourism destinations in emerging countries. This underlines the specific drivers and barriers related to CE as a sustainable development practice. Additionally, it contributes to the academic debate on this notion.
Recent Advances in Toxoplasma gondii Infection and Toxoplasmosis
Authors: Vilela Vinícius Longo Ribeiro , Feitosa Thais Ferreira
Published: July 2024

Toxoplasmosis, caused by the protozoan Toxoplasma gondii, affects nearly all warm-blooded animals, including humans, domestic animals, and both terrestrial and marine wildlife [...]
Resilient Urban-Design Strategies for Landslide Risk Mitigation in Huaraz, Peru
Authors: Esenarro Doris , Manosalva John , Sanchez Lizeth , Vargas Carlos , Raymundo Vanessa , Ccalla Jimena
Published: July 2024

The present research aims to propose resilient urban-design strategies to mitigate the risk of landslides in Huaraz. This study addresses the growing challenge of climate change and its influence on the occurrence of avalanches in Huaraz, Peru. The methodology employed included a literature review, site analysis using digital tools, and the formulation of resilient urban-design strategies. As a result, a Master Plan for Urban Resilience is proposed, using a detailed literature review, climate studies, and topographic evaluation to design urban strategies that enhance the city’s sustainability and safety. The proposed interventions, including channel expansion, installation of gabions and containment meshes, reforestation, and strategic relocation of housing, demonstrate significant potential to reduce vulnerability to avalanches. This multidisciplinary approach underscores the necessity of integrating urban adaptations in response to extreme climate variations in the Andean regions. The proposal stands out for its innovation and resilience, precisely aligning with the unique characteristics of Huaraz. The comprehensive strategy not only focuses on urban regeneration and risk prevention but also aims to significantly improve the community’s quality of life.
Intranasally Inoculated SARS-CoV-2 Spike Protein Combined with Mucoadhesive Polymer Induces Broad and Long-Lasting Immunity
Authors: Honda Tomoko , Toyama Sakiko , Matsumoto Yusuke , Sanada Takahiro , Yasui Fumihiko , Koseki Aya , Kono Risa , Yamamoto Naoki , Kamishita Takashi , Kodake Natsumi , Miyazaki Takashi , Kohara Michinori
Published: July 2024

Current mRNA vaccines against SARS-CoV-2 effectively induce systemic and cell-mediated immunity and prevent severe disease. However, they do not induce mucosal immunity that targets the primary route of respiratory infection, and their protective effects wane after a few months. Intranasal vaccines have some advantages, including their non-invasiveness and the additional ability to activate mucosal immunity. In this study, we aimed to explore the effectiveness of an intranasally inoculated spike protein of SARS-CoV-2 mixed with a carboxy-vinyl polymer (S–CVP), a viscous agent. Intranasally inoculated S–CVP strongly induced antigen-specific IgG, including neutralizing antibodies, in the mucosal epithelium and serum and cellular immunity compared to the spike protein mixed with aluminum potassium sulfate. Furthermore, IgA production was detected only with S–CVP vaccination. S–CVP-inoculation in mice significantly suppressed the viral load and inflammation in the lung and protected mice against SARS-CoV-2 challenges, including an early circulating strain and the Omicron BA.1 variant in a manner dependent on CD8+ cells and monocytes/neutrophils. Surprisingly, high antibody responses and protective effects against multiple variants of SARS-CoV-2, including Omicron BA.5, persisted for at least 15 months after the S–CVP immunization. Hence, we propose intranasal inoculation with S–CVP as a promising vaccine strategy against SARS-CoV-2.
SARS-CoV-2 Vaccines: The Advantage of Mucosal Vaccine Delivery and Local Immunity
Authors: Tobias Joshua , Steinberger Peter , Wilkinson Joy , Klais Gloria , Kundi Michael , Wiedermann Ursula
Published: July 2024

Immunity against respiratory pathogens is often short-term, and, consequently, there is an unmet need for the effective prevention of such infections. One such infectious disease is coronavirus disease 19 (COVID-19), which is caused by the novel Beta coronavirus SARS-CoV-2 that emerged around the end of 2019. The World Health Organization declared the illness a pandemic on 11 March 2020, and since then it has killed or sickened millions of people globally. The development of COVID-19 systemic vaccines, which impressively led to a significant reduction in disease severity, hospitalization, and mortality, contained the pandemic’s expansion. However, these vaccines have not been able to stop the virus from spreading because of the restricted development of mucosal immunity. As a result, breakthrough infections have frequently occurred, and new strains of the virus have been emerging. Furthermore, SARS-CoV-2 will likely continue to circulate and, like the influenza virus, co-exist with humans. The upper respiratory tract and nasal cavity are the primary sites of SARS-CoV-2 infection and, thus, a mucosal/nasal vaccination to induce a mucosal response and stop the virus’ transmission is warranted. In this review, we present the status of the systemic vaccines, both the approved mucosal vaccines and those under evaluation in clinical trials. Furthermore, we present our approach of a B-cell peptide-based vaccination applied by a prime-boost schedule to elicit both systemic and mucosal immunity.
Energy Consumption Estimation Method of Battery Electric Buses Based on Real-World Driving Data
Authors: Wang Peng , Liu Qiao , Xu Nan , Ou Yang , Wang Yi , Meng Zaiqiang , Liu Ning , Fu Jiyao , Li Jincheng
Published: July 2024

The estimation of energy consumption under real-world driving conditions is a prerequisite for optimizing bus scheduling and meeting the requirements of route operation, thereby promoting the large-scale application of battery electric buses. However, the limitation of data accuracy and the uncertainty of many factors, such as weather conditions, traffic conditions, and driving styles, etc. make accurate energy consumption estimation complicated. In response to these challenges, a new method for estimating the energy consumption of battery electric buses (BEBs) is proposed in this research. This method estimates the speed profiles of different driving styles and the energy consumption extremes using real-world driving data. First, this research provides the constraints on speed formed by environmental factors including weather conditions, route characteristics, and traffic characteristics. On this basis, there are two levels of estimation for energy consumption. The first level classifies different driving styles and constructs the corresponding speed profiles with the time interval (10 s), the same as real-world driving data. The second level further constructs the speed profiles with the time interval of 1 s by filling in the first-level speed profiles and estimating the energy consumption extremes. Finally, the estimated maximum and minimum value of energy consumption were compared with the true value and the results showed that the real energy consumption did not exceed the extremes we estimated, which proves the method we proposed is reasonable and useful. Therefore, this research can provide a theoretical foundation for the deployment of battery electric buses.
Audit of the effectiveness of a quality management system or its processes?
Authors: Aksenova Ludmyla
Published: July 2024

Guided by the provisions of DSTU ISO 9000, the article defines the objects of internal audit (hereinafter audit) and proves the choice of these objects for estimation of their effectiveness. It is determined that the audit of a quality management system (QMS) effectiveness is performed to establish its generalized evaluation, which is used by top management to make strategic decisions, and the audit of the QMS processes effectiveness is to establish evaluations for each process, which are used by middle managers to make operational decisions. The difference between corrective actions and actions to improve the effectiveness of the audited objects is shown. It is established that to improve the effectiveness of the QMS, strategic (long-term) quality objectives are developed, and to improve its processes, operational quality objectives are developed. Practical examples are provided to illustrate the conclusions. The obtained results of the study are the basis for creating a procedure for evaluating the effectiveness of the QMS and its processes during the audit.
Navier – Stokes equation for modeling the development of production factors
Authors: Kuznetsov S. B.
Published: July 2024

This article is devoted to mathematical modeling of the development of the main factors of production under the influence of investment speed. The issue of the influence of state, interstate and natural restrictions on economic growth is considered through an analysis of the relationship between factors of production. The article presents the concept of the resistance tensor of the economic environment, which allows us to take into account the impact of changes in economic policy on the development of factors of production. When constructing the resistance tensor, an attempt is made to reflect the influence on economic development of external and internal factors of the national economy, such as tax policy, competition and the banking system, customs legislation, sanctions, etc. An important point in the article is the equations connecting the rate of investment development and the rate of change in the main factors of production in an economic object. By analyzing this relationship, one can better understand the dynamics of economic development and the possible factors influencing it.

The article also proposes a new system of economic growth equations, which uses the resistance tensor of the economic environment, similar to the vector Navier – Stokes equation. However, solving the nonlinear Navier – Stokes equation remains a difficult task, so it is proposed to use an approach with piecewise constant coefficients describing the state of the economic environment. This allows us to take into account non-stationary processes and the distribution of the rate of investment development. The work highlights the importance of mathematical modeling for understanding the development of the main factors of production in the national economy. Taking into account the impact of resistance from the economic environment helps to improve our understanding of the dynamics of economic growth and identify the factors that have the greatest impact on this process.
A Comprehensive Approach to Combat GPS Spoofing and Ensure Security Positioning in Autonomous Vehicles
Authors: Kenioua Laid , Lejdel Brahim , Abdelhamid Nedioui Mohamed
Published: July 2024

The emergence of Autonomous Vehicles (AVs) marks a significant turning point in the future of transportation and reflects radical advancements in artificial intelligence, edge computing, advanced sensing systems, and advanced control. These vehicles have sophisticated sensors, artificial intelligence systems, and computing capabilities that enable them to drive and operate without human intervention. They rely on various technologies such as cameras, radar, and GPS to obtain precise information about their surroundings and make real-time decisions. However, AVs face several unique challenges. They depend on accurate and reliable location information to drive and operate, ensuring safe driving and real-time decision-making. One of the major challenges is that central positioning systems are vulnerable to attacks, security breaches, spoofing attacks, and signal jamming, which can tamper with vehicle command systems. The significance of accurately determining the vehicle’s location lies in improving driving precision, efficient decision-making, enhanced mobility in different environments, and ensuring constant communication among vehicles for better collective performance. In this research, we propose an engineering model based on mixed collaboration for secure measurement in autonomous vehicle positioning. This collaboration enhances cooperation among vehicles, where the leader obtains its location through satellite identification, and the rest of the group members depend on the leader’s location to determine their positions in a highly reliable and immune manner against GPS spoofing, signal jamming, and fraudulent attacks. Additionally, to ensure secure communication among different vehicles, a strong encryption system has been adopted to send messages within the proposed framework, ensuring higher reliability. The technique used is lightweight and robust because it uses only one operation of multiplication and only one exponential operation. Moreover, network traffic analysis and the complexity of different algorithms have been assessed to ensure the efficiency and effectiveness of the proposed framework.
Integration of Islam and Science in Interdisciplinary Islamic Studies
Authors: Hosaini Hosaini , Akhyak Akhyak
Published: July 2024

This research is very interesting and important to study according to the rational reasons stated in the background content, that science and Islam are knowledge obtained through different epistemological sources. even though in the Islamic view it is explained that Islam is a religion of salvation that does not separate science into dichotomous boxes. This research aims to construct the concept that science and Islam are sciences that originate from an epistemology originating from the creator, namely Allah SWT. This research uses a literature review (SLR) system which includes accredited national journals and several other international journals which includes several stages as follows: a. identification phase. B. filtering phase c. feasibility stage and d. inclusion and extraction phases. Based on the results of data analysis, the resulting research findings are that the Al-Qur'an provides quite high encouragement to develop sciences based on Allah's revelation and sciences based on reason. The knowledge that comes from Allah's revelation is the Koran, while the knowledge that comes from reason is the result of human thought which is developed systematically and scientifically. Thus, it can be concluded that the ulumul Qur'an perspective between science and Islam has been explained in the Qur'an through kauliyah verses which explain its relationship with the universe. Meanwhile, the second verse is the qauniyah verse which is a verse from Allah apart from discussing the universe
Sustainable Development: Implementation of The Talqin Method In Memorizing The Quran
Authors: Rahman Ikhwan , Kustati Martin , Sepriyanti Nana
Published: July 2024

The Quran is the holy book of Muslims which has a central role in human spiritual and moral life. Memorizing the Quran is a form of noble practice recommended by the Prophet Muhammad. Various methods have been developed to help the process of memorizing the Quran, one that has been proven effective for centuries is the Talqin method. This research aims to examine the implementation of the Talqin method in memorizing the Koran. The research method used is Systematic Literature Review (SLR) by analyzing 30 reputable journals published over the last five years (2019-2024). Data sources were obtained from scientific databases such as Google Scholar, ScienceDirect, Scopus and DOAJ. The findings show that the Talqin method has proven effective in helping students memorize the Quran quickly and accurately. This method has also been proven to increase students' understanding of the meaning of the Koran and build strong relationships between teachers and students. This can be seen in the factors that support the successful implementation of the Talqin method such as; teacher skills, student motivation, conducive learning environment. However, there are several challenges that need to be considered in its implementation, such as the time required, teacher availability, facilities and infrastructure. It is hoped that this research can provide a valuable contribution to the development of Islamic education practices and tahfidz of the Quran, so that it can produce a generation of Qur'anists who have noble character and love the Quran.
KAJIAN BANJIR BANDANG DI PADANG PANJANG MELALUI TINJAUAN PETA SUNGAI
Authors: Yanto Andri , Efendi Efendi , Amarullah Taufik Abdul Hasan , Putra Dino Adi , Hardewiyani Titik , Oktamalasendi Unik
Published: July 2024

The second flash flood in Ten Koto District, Tanah Datar Regency occurred in the same place in Lembah Anai Village. The large water discharge and high flow speed caused the river to overflow and worried the residents living around the river. This was due to the very high intensity of rain in the river catchment area of ​​Lembah Anai Village which fell an hour earlier. This flash flood condition is a historic phenomenon because this is the second time. The first flash flood occurred in the Anai Valley. In 1892, the Anai Valley was also hit by a major flood. This research uses a quantitative descriptive method by making a comparative study of rivers in the Sepuluh Koto District area. The research results show that the river morphology in Lembah Anai Village has the highest catchment area of ​​400 meters above sea level (MDPL), which is the widest of the surrounding rivers and decreases in the downstream area of ​​20-meter MDPL. The highest order of average bandang potential scores is first, namely the Lembah Anai Village River, second to the Kayutanam Village River, and third to the Sicincin River. The disruption of transportation routes disrupted food supplies. Ingredients such as vegetables, potatoes and meat cannot be sent through the Anai Valley. As a result, all foodstuffs in the cities of Padang and Bukittinggi experienced price increases for months because reconstruction efforts were long and expensive.
Штучний ройовий інтелект
Authors: Омельяненко Ярослав Вікторович , Сініцин Ігор Петрович
Published: July 2024

У статті розглянуто, як штучний інтелект у формі рою може розвиватися завдяки еволюційним алгоритмам, спрямованим на зменшення сенсорного здивування системи. Продемонстровано використання принципу вільної енергії, запозиченого зі статистичної фізики, для кількісного опису оптимізаційного методу (зменшення сенсорного здивування), який може бути застосований для підтримки постійного навчання. Описано способи інтегрування цього оптимізаційного методу з еволюційними алгоритмами для прискорення розвитку спеціалізованих штучних нейронних мереж (ШНМ), які визначають пропріоцептивну конфігурацію певних роботизованих елементів рою. Розглянуто, як оптимізація вільної енергії може сприяти гомеостазу ройової системи, забезпечуючи її здатність залишатися в межах сенсорних обмежень протягом активного життя. Представлено методи створення складних розподілених когнітивних систем як ієрархічної модульної системи, що складається зі спеціалізованих мікроінтелектуальних агентів, пов’язаних між собою каналами обміну інформацією. Розглянуто коеволюцію різноманітних роботизованих елементів рою, що зумовлює розвиток пропріоцепції та глибоке розуміння властивостей середовища. Також коротко описано, як ця система може бути втілена в реальність, та досягнення в цій області.
DECOUPLING A SYSTEM OF LINEAR DIFFERENTIAL EQUATIONS INTO BLOCKS
Authors: Bazylevych Yu.M. ,   Ukrainian State University of Science and Technologies, Dnipro, Ukraine, bazilvch@ukr.net, Kostiushko I.A. , Stanina O.D. , Tkachov V.S. ,   National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, Kyiv, Ukraine, kostushkoia5@gmail.com,   Dnipro University of Technology, Dnipro, Ukraine, st.olga.d@gmail.com,   Ukrainian State University of Science and Technologies, Dnipro, Ukraine,  tkachov.volodymyr@pdaba.edu.ua
Published: July 2024

Problems on reducing a system of linear differential equations to several independent low-order subsystems are considered. Construction of the auxiliary square matrices for which similarity transformation is applied is substantiated. This allows transferring the results obtained for the problem of reducing two square matrices to different classes of problems: obtaining the maximum possible number of blocks, proof of the unity of the obtained decoupling, detection of the symmetry of the system under study, detection of loosely coupled subsystems, and creation of efficient computational splitting algorithms. Keywords: matrices, systems of equations, decomposition, maximum number of subsystems.
Local identity and residents' attitudes towards innovation in sustainable tourism - the example of generation Z
Authors: Niezgoda Agnieszka , Szymańska Elżbieta
Published: July 2024

The aim of this article is to identify the attitudes of tourism region residents from generation Z presenting local identity and relate them to innovation, which shapes the product in the sustainable tourism context. A qualitative empirical study was carried out using the focus group interview method, divided into residents representing large centres, medium-sized towns and villages. The research yielded new information stating that young people have a sense of local identity and are attached to their place of residence with no relation to the type (and size) of residence. The research also showed respondents generally expect innovations to be introduced in tourism services and infrastructure, as they see the importance of innovations for building tourism attractiveness and improving the economic situation, which is in line with the idea of sustainable tourism. It, therefore, becomes important for authorities and managers to understand the local identity in the attitude of residents towards tourism innovation.