bluuebunny/crossref_metadata_2025 huggingface dataset:
Fine-Auth: A Fine-Grained User Authentication and Key Agreement Protocol Based on Physical Unclonable Functions for Wireless Body Area Networks
Authors: Liu Kaijun , Cao Qiang , Xu Guosheng , Xu Guoai
Published: November 2023

Wireless body area networks (WBANs) can be used to realize the real-time monitoring and transmission of health data concerning the human body based on wireless communication technology. With the transmission of these sensitive health data, security and privacy protection issues have become increasingly prominent. Fine-grained authentication allows physicians to run authentication checks of another specific entity according to their identifying attributes. Hence, it plays a key role in preserving the security and privacy of WBANs. In recent years, substantial research has been carried out on fine-grained authentication. However, these studies have put considerable effort into WBAN performances, resulting in weakened security. This paper proposes a fine-grained user authentication and key agreement protocol based on physical unclonable functions (PUFs) while maintaining robust security and performance. This will allow physicians to perform mutual authentication and obtain key agreements with authorized body area sensor nodes according to their identity parameters, such as occupation type and title. We then provide comprehensive security and heuristic analyses to demonstrate the security of the proposed protocol. Finally, the performance comparison shows that the proposed protocol is more robust in security, cost-effective communication, and computational overheads compared to three leading alternatives.
Evaluation Model of Holographic Communication Experience in the 6G Era Based on Light Field Display
Authors: Hou Wenjun , Bai Bing , Lyu Linkai
Published: November 2023

Holographic communication is considered one of the typical scenarios in the 6G era. Studies have shown that the light field display is considered the most effective naked-eye 3D display method in the 6G era. Despite this, there are still many issues worthy of study. Since there are currently no experience-evaluation standards for holographic communications proposed worldwide, this also causes a lot of research work to remain at the design level and vision. To truly realize the holographic communication scenario, it is necessary to systematically evaluate the light field display technology. The level of user experience determines the value of the holographic communication scenario. This requires quantifying the user’s experience level and mapping it to the technical parameters of the light field display image. However, there is still room for improvement in related research. This paper proposes a model based on semi-supervised learning, which takes light field image data of various scenes as input and uses three experience scores of comfort, space, and realism as output to complete the subjective experience evaluation of light field images. Compared with evaluation methods that focus on the quality of the image itself, this article focuses more on the effect on human experience. Compared with existing work, this paper makes improvements in two respects: feature engineering and training strategies. In terms of feature selection, the convolutional neural network is used to extract image content features, and the image quality parameter-extraction module is used to extract image property features. The two are spliced as the input of the classifier; in terms of the training strategy, pseudo-labels and dynamic thresholds are used for training. The final experimental results show that on the MPI-LFA data set, the comfort dimension’s classification accuracy is 80.21, the spatial dimension’s classification accuracy is 83.12, and the realism dimension’s classification accuracy is 81.88.
Perspectives on Digital Transformation Initiatives in the Mechanical Engineering Industry
Authors: Miklosik Andrej , Krah Alexander Bernhard
Published: November 2023

Companies from the mechanical engineering industry are eager to embrace new technologies in their pursuit of a competitive advantage. However, the complete digitalization of the sector encounters limitations, as certain aspects necessitate human supervision or manual labor. This is where the concepts of Industry 4.0, Industry 5.0, and digital transformation become relevant. The aim of the research presented in this paper was to gather and extract valuable insights and lessons from the experiences of German companies in the plastic extrusion machinery sector with digital transformation (DT). Qualitative interpretative research was used, using in-depth expert interviews with C-level executives. We organized the findings into three categories: (i) DT communication initiatives, including the elimination of paper, CRM solutions, messenger services, home office, and online procurement platforms; (ii) departments and areas most involved, including accounting and procurement, sales and production, and construction; and (iii) cost–benefit perception, including positive assessment, long-term impacts, and variation from company to company. The results provide valuable insights into the progress of DT initiatives in companies operating in the pipe extrusion sector in Germany. Additionally, several DT misconceptions were identified, thereby enriching the DT misconceptions framework that has been intensely discussed in the DT literature.
Numerical Analysis of an Innovative Double-Strap Joint for the Splicing of Near-Surface Mounted Fiber-Reinforced Polymer Bars for Reinforced Concrete Beam Strengthening
Authors: Ranković Slobodan , Zorić Andrija , Vacev Todor , Petrović Žarko
Published: November 2023

The issue of the cut-off splicing of an additional fiber-reinforced polymer (FRP) bar in the near-surface mounted (NSM) technique for reinforced concrete (RC) beam strengthening exposed dominantly to bending is insufficiently investigated. A possible solution of this issue is a new proposed technique: a double-strap joint. It implies the widening of the groove at the cut-off location and the symmetrical installing of additional supplements of FRP reinforcement. In this research, beam strength has been determined for the following cases: additional NSM FRP reinforcement without a cut-off, with a cut-off, and without overlapping, and with different lengths of splice overlapping. A nonlinear analysis based on the finite element method (FEM) has been applied. The length of the cut-off splice of the additional FRP reinforcement with glass fibers (GFRP) was 20Ø, 40Ø, and 60Ø. The validation of the numerical model and a comparison of the results were conducted by using the authors’ experiments. It has been shown that, in the case of a cut-off of NSM GFRP bars, a significant loss in strengthening efficiency occurs, and that, with an increase in the overlapping length, this loss decreases. An overlapping length of 60Ø provides full strengthening. An efficiency assessment was carried out via the use of a parametric study, varying the FRP bar material type and its diameter for a constant splicing length.
Methodology for CubeSat Debris Collision Avoidance Based on Its Active ADCS System
Authors: González-Rodríguez Desiree , Orgeira-Crespo Pedro , Cappelletti Chantal , Aguado-Agelet Fernando
Published: November 2023

This research assesses the feasibility of a collision avoidance methodology for CubeSats lacking propulsion. The approach involves altering the satellite’s orientation to modify its cross-sectional area and, subsequently, the drag force. Examining altitudes within low Earth orbit (LEO) across 2U, 3U, and 6U CubeSat formats, maneuvers are considered two days before the Time to Closest Approach (TCA). Evaluation against the Conjunction Data Messages (CDMs) threshold miss distances reveals a minimum 7% and maximum 106% deviation in Vertical Distance Difference (VDD), and 68% to 1045% in Horizontal Distance Difference (HDD) concerning the notification threshold. These findings strongly endorse the practicality of the proposed collision avoidance methodology, utilizing CubeSat Attitude Determination and Control Systems (ADCS). Ongoing research focuses on assessing ADCS maneuver execution rates and implementation times, advancing our understanding and applicability of this innovative CubeSat collision avoidance approach.
Enhanced Temporal Knowledge Graph Completion via Learning High-Order Connectivity and Attribute Information
Authors: Wen Minwei , Mei Hongyan , Wang Wei , Zhang Xing
Published: November 2023

Temporal knowledge graph completion (TKGC) refers to the prediction and filling in of missing facts on time series, which is essential for many downstream applications. However, many existing TKGC methods suffer from two limitations: (1) they only consider direct relations between entities and fail to express high-order structural dependencies between entities; and (2) they only leverage relation quadruples of temporal knowledge graphs, ignoring attribute information that contains rich semantic information. This makes them vulnerable to sparsity and incompleteness problems. In response, we propose HCAE, a temporal knowledge graph completion model that includes high-order connectivity and attribute information. This consists mainly of a recursive embedding propagation layer and a multi-head attention aggregation layer. The former leverages a recursive mechanism to update entity embeddings and can learn high-order connectivity information between entities in linear complexity time. The latter leverages an attention mechanism to understand the importance of different attributes for entity representation automatically. Combining high-order connectivity and attribute information can lead to more diverse entity representations and help enhance the model’s ability to infer unknown entities. Comparative experiments on three real-world datasets show that the model’s inference accuracy significantly outperforms other benchmark methods, especially regarding knowledge graphs with many unknown entities or relations.
Comparison of Sunshine Duration Measurements between the Campbell–Stokes Sunshine Recorder and Three Automatic Sensors at Three Locations in Cyprus
Authors: Pashiardis Stelios , Pelengaris Alexandros , Kalogirou Soteris A.
Published: November 2023

This paper compares the daily sunshine duration (SD) measured by the Campbell–Stokes sunshine recorder (CS) with three automatic instruments (Kipp & Zonen pyranometers (CM6 B), pyrheliometer (CHP1) and CSD3 sunshine recorders). The comparisons are essential, since recently, automatic sunshine duration sensors have been replacing the manual measurements, affecting, therefore, the continuity of the CS time series. The comparisons were applied to the daily SD data of three synoptic stations (Larnaca A/P, Pafos A/P and Athalassa) where parallel measurements of manual and automatic instruments are carried out during the periods 2009–2012 and 2012–2015. The CSD3 measurements were obtained from two automatic weather stations (AWSs) which are close to the synoptic station of Larnaca A/P. The comparisons referred to the daily and monthly sums of sunshine duration, as well as to their statistical distributions and their relationships. The daily differences in the pairs of sunshine recorders installed at the same location are mostly within the range of −1.0 to +1.0 h. At Larnaca, in the period 2009–2012, the pyranometric method’s (Gl) values were higher than the CS in the summer months. Pafos and Athalassa showed higher values of CS compared to Gl and the pyrheliometric method (Pr), respectively, almost throughout the year. Generally, the annual average daily differences between the different pairs range between 0.3 and 0.5 h. Regression equations were determined allowing the estimation of daily SD under different sky conditions. The coefficient of determination (R2) reached the values of 0.91 and 0.96 under ‘all sky’ conditions, and between 0.80 and 0.91 under ‘clear’ sky conditions at the three locations.
LunarSim: Lunar Rover Simulator Focused on High Visual Fidelity and ROS 2 Integration for Advanced Computer Vision Algorithm Development
Authors: Pieczyński Dominik , Ptak Bartosz , Kraft Marek , Drapikowski Paweł
Published: November 2023

Autonomous lunar exploration is a complex task that requires the development of sophisticated algorithms to control the movement of lunar rovers in a challenging environment, based on visual feedback. To train and evaluate these algorithms, it is crucial to have access to both a simulation framework and data that accurately represent the conditions on the lunar surface, with the main focus on providing the visual fidelity necessary for computer vision algorithm development. In this paper, we present a lunar-orientated robotic simulation environment, developed using the Unity game engine, built on top of robot operating system 2 (ROS 2), which enables researchers to generate quality synthetic vision data and test their algorithms for autonomous perception and navigation of lunar rovers in a controlled environment. To demonstrate the versatility of the simulator, we present several use cases in which it is deployed on various efficient hardware platforms, including FPGA and Edge AI devices, to evaluate the performance of different vision-based algorithms for lunar exploration. In general, the simulation environment provides a valuable tool for researchers developing lunar rover systems.
Flavor Chemistry and Technology: The Challenges of Working with Flavors in the Food Industry
Authors: Genovese Alessandro
Published: November 2023

The term “flavor” refers to the overall sensory experience of a food or beverage, including olfaction (the perception of smell and aroma), gustation (the perception of taste), and trigeminal sensations, which combine the perception of texture, mouthfeel, temperature, and chemesthesis (i [...]
A Novel Convolutional Neural Network Deep Learning Implementation for Cuffless Heart Rate and Blood Pressure Estimation
Authors: Bossavi Géraud , Yan Rongguo , Irfan Muhammad
Published: November 2023

Cardiovascular diseases (CVDs) affect components of the circulatory system responsible for transporting blood through blood vessels. The measurement of the mechanical force acting on the walls of blood vessels, as well as the blood flow between heartbeats and when the heart is at rest, is known as blood pressure (BP). Regular assessment of BP can aid in the prevention and early detection of CVDs. In the present research, a deep learning algorithm was developed to accurately calculate both blood pressure (BP) and heart rate (HR) by extracting relevant features from photoplethysmogram (PPG), electrocardiogram (ECG), and ABP signals. This algorithm was implemented using the Medical Information Mart for Intensive Care (MIMIC-II) dataset. It captures vital blood pressure-related features extracted from the PPG signal and accounts for the time relationship with the ECG. The algorithm also determines the values of systolic blood pressure (SBP) and diastolic blood pressure (DBP) based on the ABP waveform through a convolutional neural network and stepwise multivariate linear regression. In comparison with other established BP measurement methods, our proposed approach achieved better results, with a mean absolute error (MAE) of approximately 4.7 mmHg for SBP and 2.1 mmHg for DBP, respectively. The standard deviation (STD) for SBP and DBP was approximately 7.6 mmHg and 3.9 mmHg, respectively. This study makes a valuable contribution to the healthcare field by introducing a novel, cost-effective continuous BP measurement method with improved accuracy while also minimizing the data dimension without losing any important information.
Microorganism Detection in Activated Sludge Microscopic Images Using Improved YOLO
Authors: Kong Yueping , Shen Zhiyuan
Published: November 2023

Wastewater has detrimental effects on the natural environment. The activated sludge method, a widely adopted approach for wastewater treatment, has proven highly effective. Within this process, microorganisms play a pivotal role, necessitating continuous monitoring of their quantity and diversity. Conventional methods, such as microscopic observation, are time-consuming. With the widespread integration of computer vision technologies into object detection, deep learning-based object detection algorithms, notably the You Only Look Once (YOLO) model, have garnered substantial interest for their speed and precision in detection tasks. In this research, we applied the YOLO model to detect microorganisms in microscopic images of activated sludge. Furthermore, addressing the irregular shapes of microorganisms, we developed an improved YOLO model by incorporating deformable convolutional networks and an attention mechanism to enhance its detection capabilities. We conducted training and testing using a custom dataset comprising five distinct objects. The performance evaluations used in this study utilized metrics such as the mean average precision at intersections over a union threshold of 0.5 (mAP@0.5), with the improved YOLO model achieving a mAP@0.5 value of 93.7%, signifying a 4.3% improvement over the YOLOv5 model. Comparative analysis of the improved YOLO model and other object detection algorithms on the same dataset revealed a higher accuracy for the improved YOLO model. These results demonstrate the superior performance of the improved YOLO model in the task of detecting microorganisms in activated sludge, providing an effective auxiliary method for wastewater treatment monitoring.
A Feature Selection Algorithm Based on Differential Evolution for English Speech Emotion Recognition
Authors: Yue Liya , Hu Pei , Chu Shu-Chuan , Pan Jeng-Shyang
Published: November 2023

The automatic identification of emotions from speech holds significance in facilitating interactions between humans and machines. To improve the recognition accuracy of speech emotion, we extract mel-frequency cepstral coefficients (MFCCs) and pitch features from raw signals, and an improved differential evolution (DE) algorithm is utilized for feature selection based on K-nearest neighbor (KNN) and random forest (RF) classifiers. The proposed multivariate DE (MDE) adopts three mutation strategies to solve the slow convergence of the classical DE and maintain population diversity, and employs a jumping method to avoid falling into local traps. The simulations are conducted on four public English speech emotion datasets: eNTERFACE05, Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS), Surrey Audio-Visual Expressed Emotion (SAEE), and Toronto Emotional Speech Set (TESS), and they cover a diverse range of emotions. The MDE algorithm is compared with PSO-assisted biogeography-based optimization (BBO_PSO), DE, and the sine cosine algorithm (SCA) on emotion recognition error, number of selected features, and running time. From the results obtained, MDE obtains the errors of 0.5270, 0.5044, 0.4490, and 0.0420 in eNTERFACE05, RAVDESS, SAVEE, and TESS based on the KNN classifier, and the errors of 0.4721, 0.4264, 0.3283 and 0.0114 based on the RF classifier. The proposed algorithm demonstrates excellent performance in emotion recognition accuracy, and it finds meaningful acoustic features from MFCCs and pitch.
Probabilistic Procedures for SIR and SIS Epidemic Dynamics on Erdös-Rényi Contact Networks
Authors: Rocha J. Leonel , Carvalho Sónia , Coimbra Beatriz
Published: November 2023

This paper introduces the mathematical formalization of two probabilistic procedures for susceptible-infected-recovered (SIR) and susceptible-infected-susceptible (SIS) infectious diseases epidemic models, over Erdös-Rényi contact networks. In our approach, we consider the epidemic threshold, for both models, defined by the inverse of the spectral radius of the associated adjacency matrices, which expresses the network topology. The epidemic threshold dynamics are analyzed, depending on the global dynamics of the network structure. The main contribution of this work is the relationship established between the epidemic threshold and the topological entropy of the Erdös-Rényi contact networks. In addition, a relationship between the basic reproduction number and the topological entropy is also stated. The trigger of the infectious state is studied, where the probability value of the stability of the infected state after the first instant, depending on the degree of the node in the seed set, is proven. Some numerical studies are included and illustrate the implementation of the probabilistic procedures introduced, complementing the discussion on the choice of the seed set.
Stress–Strength Reliability Analysis for Different Distributions Using Progressive Type-II Censoring with Binomial Removal
Authors: Elbatal Ibrahim , Hassan Amal S. , Diab L. S. , Ben Ghorbal Anis , Elgarhy Mohammed , El-Saeed Ahmed R.
Published: November 2023

In the statistical literature, one of the most important subjects that is commonly used is stress–strength reliability, which is defined as δ=PW<V, where V and W are the strength and stress random variables, respectively, and δ is reliability parameter. Type-II progressive censoring with binomial removal is used in this study to examine the inference of δ=PW<V for a component with strength V and being subjected to stress W. We suppose that V and W are independent random variables taken from the Burr XII distribution and the Burr III distribution, respectively, with a common shape parameter. The maximum likelihood estimator of δ is derived. The Bayes estimator of δ under the assumption of independent gamma priors is derived. To determine the Bayes estimates for squared error and linear exponential loss functions in the lack of explicit forms, the Metropolis–Hastings method was provided. Utilizing comprehensive simulations and two metrics (average of estimates and root mean squared errors), we compare these estimators. Further, an analysis is performed on two actual data sets based on breakdown times for insulating fluid between electrodes recorded under varying voltages.
Non-Invasive Wearable Devices for Monitoring Vital Signs in Patients with Type 2 Diabetes Mellitus: A Systematic Review
Authors: Piet Artur , Jablonski Lennart , Daniel Onwuchekwa Jennifer I. , Unkel Steffen , Weber Christian , Grzegorzek Marcin , Ehlers Jan P. , Gaus Olaf , Neumann Thomas
Published: November 2023

Type 2 diabetes mellitus (T2D) poses a significant global health challenge and demands effective self-management strategies, including continuous blood glucose monitoring (CGM) and lifestyle adaptations. While CGM offers real-time glucose level assessment, the quest for minimizing trauma and enhancing convenience has spurred the need to explore non-invasive alternatives for monitoring vital signs in patients with T2D. Objective: This systematic review is the first that explores the current literature and critically evaluates the use and reporting of non-invasive wearable devices for monitoring vital signs in patients with T2D. Methods: Employing the PRISMA and PICOS guidelines, we conducted a comprehensive search to incorporate evidence from relevant studies, focusing on randomized controlled trials (RCTs), systematic reviews, and meta-analyses published since 2017. Of the 437 publications identified, seven were selected based on predetermined criteria. Results: The seven studies included in this review used various sensing technologies, such as heart rate monitors, accelerometers, and other wearable devices. Primary health outcomes included blood pressure measurements, heart rate, body fat percentage, and cardiorespiratory endurance. Non-invasive wearable devices demonstrated potential for aiding T2D management, albeit with variations in efficacy across studies. Conclusions: Based on the low number of studies with higher evidence levels (i.e., RCTs) that we were able to find and the significant differences in design between these studies, we conclude that further evidence is required to validate the application, efficacy, and real-world impact of these wearable devices. Emphasizing transparency in bias reporting and conducting in-depth research is crucial for fully understanding the implications and benefits of wearable devices in T2D management.
Gesture Classification in Electromyography Signals for Real-Time Prosthetic Hand Control Using a Convolutional Neural Network-Enhanced Channel Attention Model
Authors: Yu Guangjie , Deng Ziting , Bao Zhenchen , Zhang Yue , He Bingwei
Published: November 2023

Accurate and real-time gesture recognition is required for the autonomous operation of prosthetic hand devices. This study employs a convolutional neural network-enhanced channel attention (CNN-ECA) model to provide a unique approach for surface electromyography (sEMG) gesture recognition. The introduction of the ECA module improves the model’s capacity to extract features and focus on critical information in the sEMG data, thus simultaneously equipping the sEMG-controlled prosthetic hand systems with the characteristics of accurate gesture detection and real-time control. Furthermore, we suggest a preprocessing strategy for extracting envelope signals that incorporates Butterworth low-pass filtering and the fast Hilbert transform (FHT), which can successfully reduce noise interference and capture essential physiological information. Finally, the majority voting window technique is adopted to enhance the prediction results, further improving the accuracy and stability of the model. Overall, our multi-layered convolutional neural network model, in conjunction with envelope signal extraction and attention mechanisms, offers a promising and innovative approach for real-time control systems in prosthetic hands, allowing for precise fine motor actions.
Toll-like Receptor 9 Gene in the Development of Type 2 Diabetes Mellitus in the Saudi Arabian Population
Authors: Alkudmani Zeina S. , Alzailai Aminah Ahmad , Aburisheh Khaled H. , Alshammary Amal F. , Ali Khan Imran
Published: November 2023

Diabetes mellitus is a complex disease with a wide range of manifestations. Diabetes, notably type 2 diabetes mellitus (T2DM), is becoming more common in Saudi Arabia as a result of obesity and an aging population. T2DM is classified as a noncommunicable disease, and its incidence in the Saudi population continues to grow as a consequence of socioeconomic changes. Toll-like receptors (TLRs) are innate immune receptors that mediate the inflammatory response in diabetes mellitus. Previous studies have documented the relationship between different SNPs in the TLR9 gene in different forms of diabetes. As a result, the purpose of this study was to investigate the relationship between rs187084, rs352140, and rs5743836 SNPs in the TLR9 gene among T2DM patients in the Saudi population. This was a case-control study that included 100 T2DM cases and 100 control subjects. The three SNPs were identified in the study population (n = 200) using polymerase chain reaction (PCR), restriction enzymes for rs352140, and Sanger sequencing for rs187084 and rs5783836. Next, statistical analyses were performed using various software to determine the association between the SNPs and T2DM. rs187084 and rs5743836 were associated with an increased risk of T2DM development. rs187084 and rs5743836 allelic frequencies were associated with a 3.2 times increased risk of T2DM development (p < 0.05). DBP was associated with T2DM (p = 0.02). rs187084 was associated with TC and HDLc; rs352140 was associated with DBP, HbA1c, and HDLc; rs5743836 was associated with waist (p < 0.05). The CGT haplotype was strongly associated with T2DM (p < 0.003). Gene–gene interaction, graphical presentation, and dendrogram showed the strong association with T2DM patients (p < 0.05). This study concluded that rs187084 and rs5743836 were strongly associated with T2DM in Saudi Arabian patients. This study provides further evidence that SNPs in the TLR9 gene play a significant role in T2DM development in a Saudi community.
DPH1 Gene Mutations Identify a Candidate SAM Pocket in Radical Enzyme Dph1•Dph2 for Diphthamide Synthesis on EF2
Authors: Ütkür Koray , Schmidt Sarina , Mayer Klaus , Klassen Roland , Brinkmann Ulrich , Schaffrath Raffael
Published: November 2023

In eukaryotes, the Dph1•Dph2 dimer is a non-canonical radical SAM enzyme. Using iron-sulfur (FeS) clusters, it cleaves the cosubstrate S-adenosyl-methionine (SAM) to form a 3-amino-3-carboxy-propyl (ACP) radical for the synthesis of diphthamide. The latter decorates a histidine residue on elongation factor 2 (EF2) conserved from archaea to yeast and humans and is important for accurate mRNA translation and protein synthesis. Guided by evidence from archaeal orthologues, we searched for a putative SAM-binding pocket in Dph1•Dph2 from Saccharomyces cerevisiae. We predict an SAM-binding pocket near the FeS cluster domain that is conserved across eukaryotes in Dph1 but not Dph2. Site-directed DPH1 mutagenesis and functional characterization through assay diagnostics for the loss of diphthamide reveal that the SAM pocket is essential for synthesis of the décor on EF2 in vivo. Further evidence from structural modeling suggests particularly critical residues close to the methionine moiety of SAM. Presumably, they facilitate a geometry specific for SAM cleavage and ACP radical formation that distinguishes Dph1•Dph2 from classical radical SAM enzymes, which generate canonical 5′-deoxyadenosyl (dAdo) radicals.
Clinical Validation of Estimated Muscle Activations during Phases of Elderly Gait
Authors: Gkrekidis Athanasios , Giarmatzis Georgios , Menychtas Dimitrios , Karakasis Evangelos , Gourgoulis Vassilios , Michalopoulou Maria , Smilios Ilias , Douda Helen T. , Sirakoulis Georgios Ch. , Aggelousis Nikolaos
Published: November 2023

This study validated muscle activation estimations generated by OpenSim during the gait of elderly fallers. Ten healthy elderly participants walked on an instrumented treadmill, monitored by motion capture, force platforms, and 12 surface EMG sensors. Static optimization was used to calculate muscle activations, evaluated through cosine similarity, comparing them with EMG signals from 12 muscles of the right leg. Findings revealed varied similarity levels across muscles and gait phases. During stance phase, tibialis anterior (TIBA), peroneus longus (PERL), soleus (SOL), gastrocnemius lateralis (GASL), semitendinosus (SEMI), tensor fasciae latae (TFL), and rectus femoris (RECF) demonstrated poor similarity (cosim < 0.6), while gluteus medius (GMED), biceps femoris long head (BFLH), and vastus lateralis (VL) exhibited moderate similarity (0.6 ≤ cosim ≤ 0.8), and gluteus maximus (GMAX) and vastus medialis (VASM) displayed high similarity (cosim > 0.8). During the swing phase, only SOL demonstrated inadequate similarity, while GASL, GMAX, GMED, BFLH, SEMI, TFL, RECF, and VASL exhibited moderate similarity, and TIBA, PERL, and VASM showed high similarity. Comparing the different 10% intervals of the gait cycle generally produced more favorable similarity results. For most of the muscles and intervals, good agreement was found. Moderate agreement was estimated in the cases of TIBA (0–10%), PERL (60–70%), GASL (60–70%), TFL (10–20%), RECF (0–10%, 80–100%), and GMED (50–60%). Bad agreement was found in the cases of SOL (60–70%), GASL (0–10%), and TFL (0–10%). In conclusion, the study’s validation outcomes were acceptable in most cases, underlining the potential for user-friendly musculoskeletal modeling routines to study muscle output during elderly gait.
Hemoadsorption as Adjuvant Therapy in Acute Respiratory Distress Syndrome (ARDS): A Systematic Review and Meta-Analysis
Authors: Szigetváry Csenge Erzsébet , Turan Caner , Kovács Emőke Henrietta , Kói Tamás , Engh Marie Anne , Hegyi Péter , Csukly Gábor , Ruszkai Zoltán , Molnár Zsolt
Published: November 2023

Background: Acute respiratory distress syndrome (ARDS) is often a consequence of a dysregulated immune response; therefore, immunomodulation by extracorporeal cytokine removal has been increasingly used as an adjuvant therapy, but convincing data are still missing. The aim of this study was to investigate the effects of adjunctive hemoadsorption (HA) on clinical and laboratory outcomes in patients with ARDS. Methods: We performed a systematic literature search in PubMed, Embase, CENTRAL, Scopus, and Web of Science (PROSPERO: CRD42022292176). The population was patients receiving HA therapy for ARDS. The primary outcome was the change in PaO2/FiO2 before and after HA therapy. Secondary outcomes included the before and after values for C-reactive protein (CRP), lactate, interleukin-6 (IL-6), and norepinephrine (NE) doses. Results: We included 26 publications, with 243 patients (198 undergoing HA therapy and 45 controls). There was a significant improvement in PaO2/FiO2 ratio following HA therapy (MD = 68.93 [95%-CI: 28.79 to 109.06] mmHg, p = 0.005) and a reduction in CRP levels (MD = −45.02 [95%-CI: −82.64; −7.39] mg/dL, p = 0.026) and NE dose (MD = −0.24 [95%-CI: −0.44 to −0.04] μg/kg/min, p = 0.028). Conclusions: Based on our findings, HA resulted in a significant improvement in oxygenation and a reduction in NE dose and CRP levels in patients treated with ARDS. Properly designed RCTs are still needed.
Preparation, Physicochemical Characterization, Antimicrobial Effects, Biocompatibility and Cytotoxicity of Co-Loaded Meropenem and Vancomycin in Mesoporous Silica Nanoparticles
Authors: Yekani Mina , Azargun Robab , Sharifi Simin , Sadri Nahand Javid , Hasani Alka , Ghanbari Hadi , Sadat Seyyedi Zahra , Memar Mohammad Yousef , Maleki Dizaj Solmaz
Published: November 2023

Mesoporous silica nanoparticles (MSNPs) have been reported as an effective system to co-deliver a variety of different agents to enhance efficiency and improve biocompatibility. This study was aimed at the preparation, physicochemical characterization, antimicrobial effects, biocompatibility, and cytotoxicity of vancomycin and meropenem co-loaded in the mesoporous silica nanoparticles (Van/Mrp-MSNPs). The prepared nanoparticles were explored for their physicochemical features, antibacterial and antibiofilm effects, biocompatibility, and cytotoxicity. The minimum inhibitory concentrations (MICs) of the Van/Mrp-MSNPs (0.12–1 µg/mL) against Staphylococcus aureus isolates were observed to be lower than those of the same concentrations of vancomycin and meropenem. The minimum biofilm inhibitory concentration (MBIC) range of the Van/Mrp-MSNPs was 8–64 μg/mL, which was lower than the meropenem and vancomycin MBICs. The bacterial adherence was not significantly decreased upon exposure to levels lower than the MICs of the MSNPs and Van/Mrp-MSNPs. The viability of NIH/3T3 cells treated with serial concentrations of the MSNPs and Van/Mrp-MSNPs were 73–88% and 74–90%, respectively. The Van/Mrp-MSNPs displayed considerable inhibitory effects against MRSA, favorable biocompatibility, and low cytotoxicity. The Van/Mrp-MSNPs could be a potential system for the treatment of infections.
Crestal and Subcrestal Placement of Morse Cone Implant–Abutment Connection Implants: An In Vitro Finite Element Analysis (FEA) Study
Authors: Comuzzi Luca , Ceddia Mario , Di Pietro Natalia , Inchingolo Francesco , Inchingolo Angelo Michele , Romasco Tea , Tumedei Margherita , Specchiulli Alessandro , Piattelli Adriano , Trentadue Bartolomeo
Published: November 2023

The issue of dental implant placement relative to the alveolar crest, whether in supracrestal, equicrestal, or subcrestal positions, remains highly controversial, leading to conflicting data in various studies. Three-dimensional (3D) Finite Element Analysis (FEA) can offer insights into the biomechanical aspects of dental implants and the surrounding bone. A 3D model of the jaw was generated using computed tomography (CT) scans, considering a cortical thickness of 1.5 mm. Subsequently, Morse cone implant–abutment connection implants were virtually positioned at the model’s center, at equicrestal (0 mm) and subcrestal levels (−1 mm and −2 mm). The findings indicated the highest stress within the cortical bone around the equicrestally placed implant, the lowest stress in the −2 mm subcrestally placed implant, and intermediate stresses in the −1 mm subcrestally placed implant. In terms of clinical relevance, this study suggested that subcrestal placement of a Morse cone implant–abutment connection (ranging between −1 and −2 mm) could be recommended to reduce peri-implant bone resorption and achieve longer-term implant success.
Synthesis, Cytotoxic, and Computational Screening of Some Novel Indole–1,2,4-Triazole-Based S-Alkylated N-Aryl Acetamides
Authors: Zahoor Ameer Fawad , Saeed Sadaf , Rasul Azhar , Noreen Razia , Irfan Ali , Ahmad Sajjad , Faisal Shah , Al-Hussain Sami A. , Saeed Muhammad Athar , Muhammed Muhammed Tilahun , Muhammad Zeinab A. , Zaki Magdi E. A.
Published: November 2023

Molecular hybridization has emerged as the prime and most significant approach for the development of novel anticancer chemotherapeutic agents for combating cancer. In this pursuit, a novel series of indole–1,2,4-triazol-based N-phenyl acetamide structural motifs 8a–f were synthesized and screened against the in vitro hepatocellular cancer Hep-G2 cell line. The MTT assay was applied to determine the anti-proliferative potential of novel indole–triazole compounds 8a–f, which displayed cytotoxicity potential as cell viabilities at 100 µg/mL concentration, by using ellipticine and doxorubicin as standard reference drugs. The remarkable prominent bioactive structural hybrids 8a, 8c, and 8f demonstrated good-to-excellent anti-Hep-G2 cancer chemotherapeutic potential, with a cell viability of (11.72 ± 0.53), (18.92 ± 1.48), and (12.93 ± 0.55), respectively. The excellent cytotoxicity efficacy against the liver cancer cell line Hep-G2 was displayed by the 3,4-dichloro moiety containing indole–triazole scaffold 8b, which had the lowest cell viability (10.99 ± 0.59) compared with the standard drug ellipticine (cell viability = 11.5 ± 0.55) but displayed comparable potency in comparison with the standard drug doxorubicin (cell viability = 10.8 ± 0.41). The structure–activity relationship (SAR) of indole–triazoles 8a–f revealed that the 3,4-dichlorophenyl-based indole–triazole structural hybrid 8b displayed excellent anti-Hep-G2 cancer chemotherapeutic efficacy. The in silico approaches such as molecular docking scores, molecular dynamic simulation stability data, DFT, ADMET studies, and in vitro pharmacological profile clearly indicated that indole–triazole scaffold 8b could be the lead anti-Hep-G2 liver cancer therapeutic agent and a promising anti-Hep-G2 drug candidate for further clinical evaluations.
The Reward-Related Shift of Emotional Contagion from the Observer’s Perspective Correlates to Their Intimacy with the Expresser
Authors: Chen Ying , Chen Wenfeng , Zhang Ling , Wei Yanqiu , Hu Ping
Published: November 2023

Although previous studies have found a bidirectional relationship between emotional contagion and reward, there is insufficient research to prove the effect of reward on the social function of emotional contagion. To explore this issue, the current study used electroencephalography (EEG) and the interactive way in which the expresser played games to help participants obtain reward outcomes. The results demonstrated a significant correlation between changes in emotional contagion and closeness, indicating that emotional contagion has a social regulatory function. Regarding the impact of reward outcomes, the results showed that compared to the context of a loss, in the context of a win, participants’ closeness toward the expresser shifted to a more intimate level, their emotional contagion changed in a more positive direction, and the activity of the late positive component (LPC) of the event-related potentials (ERPs) changed to a greater extent. Significantly, the mediation results demonstrated the effect of reward and indicated that changes in the LPC elicited while experiencing the expressers’ emotion predicted the subsequent shifts in closeness through alterations in emotional contagion of the anger emotion in the winning context and the happy emotion in the loss context. This study provides empirical evidence regarding the social function of emotional contagion and proves for the first time that the reward context plays a role in it.
The Influence of Classroom Size and Window View on Young Children’s Executive Functions and Physiological Responses, Based on VR Technology
Authors: Cha Kijoo
Published: November 2023

Despite the increasing enrollment of young children in childcare institutes, there have been few empirical studies on the effects of spatial elements on their development. This study explored the impact of preschool classroom size (large vs. small) and window view (natural vs. built environment) on young children’s executive functions and physiological stress responses, using cortisol and heart rate variability (HRV) as indicators and employing virtual reality (VR) technology. Out of 144 participants aged 61–85 months, three were excluded due to missing values and outliers. Executive function tests were administered, and saliva samples were collected before and after VR exposure; HRV data were gathered during the experience. ANCOVA results indicated significant improvements in cognitive flexibility, as measured based on the Dimensional Change Card Sorting task, in the large classroom condition, and a marginally significant decrease in visuo-spatial working memory, as measured with the Corsi block task, in the small classroom condition. The classroom size conditions did not significantly differ in cortisol response, but the large classroom condition showed marginally significant HRV indices, suggesting increased relaxation. No significant effects on executive functions or physiological responses were found in either window view condition. Overall, the findings suggest that classroom size may influence young children’s cognitive flexibility.
Fragility Analysis of the Main Building–Coal Conveyor Trestle Interaction System of a Thermal Power Plant
Authors: Hu Yang , Bai Wen , Dai Junwu , Li Qingwen
Published: November 2023

Thermal power plants play a crucial role in the power system as critical lifeline infrastructure. In order to meet the production process requirements, the main building of a thermal power plant is often connected to a coal conveyor trestle. This study focuses on investigating the seismic interaction between the common three-row reinforced concrete frame-bent main building and the steel trestle in a circulating fluidized bed (CFB) unit. The objective is to assess the influence of the trestle on the main building and understand the failure mode of the trestle structure. The seismic interaction is analyzed through fragility analysis based on Incremental Dynamic Analysis (IDA). The results indicate that the trestle has minimal influence on the main building, except during the large deformation stage. The study identifies the failure mode of the coal conveyor trestle as excessive relative displacement along the longitudinal direction at the connection points, leading to collisions or falls. A seismic demand model based on longitudinal relative displacement is developed to obtain the fragility curve for the trestle structure. These findings offer valuable insights for assessing the seismic performance of thermal power plants.
Evaluation of Flexural Behavior of Prestressed Concrete (PSC) Hollow-Core Slabs (HCSs)
Authors: Kim Dong-Hwan , Kim Min-Jun , Jo Min-Su , Kim Hyeong-Gook , Yoon Yeo-Jin , Kim Kil-Hee
Published: November 2023

This study aimed to evaluate the flexural behavior characteristics of prestressed concrete hollow-core slabs (HCSs) through bending experiments. Six specimens were used as variables, both with and without reinforced concrete, in the HCS. A four-point load was applied in the form of a simple support beam to assess the flexural behavior and ultimate strength of HCS. The results demonstrate that, compared to non-reinforced specimens, the reinforced HCS exhibited higher maximum loads and better ductility performance. The experimental outcomes demonstrate that HCS showed an average of 10% higher capacity than the maximum load of the concrete structure standards (KDS 14 20 20, ACI 318-19, and PCI handbook), with or without reinforced concrete, leading to relatively safe predictions. This study’s experimental findings are anticipated to aid in evaluating structural safety in a relatively secure way. The findings indicate that the HCS structural system is excellent at sustaining the weight of a structure and ensuring its safety. Additionally, this investigation is anticipated to furnish practical guidance for optimizing the use of HCS systems in structural design and construction.
‘Buildability’ in the Digital Age: A Phenomenological Discourse of Industry Practitioners’ Perceptions
Authors: Wimalaratne Puwakkatiya Lokuge Indrani , Kulatunga Udayangani , Gajendran Thayaparan
Published: November 2023

Since the emergence of the concept of “buildability” in 1983, numerous studies have focused on improving project performance through buildability. Initially, the buildability discourse was based on narrow definitions and focused on aspects that could improve construction performance. Although explicit academic discourse on buildability has been limited for three decades, the ongoing calls to improve construction performance have never subsided. As buildability was seen as important by industry in the 1980s and 1990s for improving performance, its limited discourse warrants investigation to understand how buildability has evolved in practice over the last 30 years. Therefore, this study aims to review and extend the discourse of the buildability concept using a phenomenological research approach to capture the unconscious evolution of the concept through stakeholder interpretations. An Interpretative Phenomenological Analysis (IPA) research philosophy embedded in the exploratory tradition was followed to uncover the 16 key underlying constructs of the buildability concept. The study is significant for casting potential buildability discourse trajectories for the future of the construction industry by integrating people, process, and technology. The findings extend the dimensions of buildability, accommodating stakeholders’ expectations and project conditions as part of buildability decisions. Moreover, the study suggests that emerging technologies (e.g., AI) will become integral to buildability processes in terms of managing knowledge in the future.
Studying the Compressed Mechanical Characteristics of a Novel Carbon-Free Plaster Using ANSYS Software
Authors: Albadrani Mohammed Aqeel , Almutairi Ahmed D.
Published: November 2023

Eco-friendly plasters offer several advantages, including sustainability, nontoxicity, and low cost. These plasters are made with sustainable materials, such as natural fibers and starches. These materials can have different mechanical properties compared to traditional plasters, which are made with gypsum and cement. Due to the increased attention being paid to environmental issues, efforts are still being made to switch out the conventional plaster of gypsum and cement for an eco-friendlier alternative to minimize toxicity, increase effectiveness, and lower cost. In this study, the effect of novel plaster behavior under pressure on mechanical properties was investigated. The plaster investigated was an eco-friendly carbon-free BSCO plaster. A range of experimental techniques were used, such as compression testing for confirmation using ANSYS 2023 R1 software, which set ergonomic and user-friendly standards as a minimum requirement, with the overarching goal of creating stronger, lighter, and more reasonably priced structures. The results showed that eco-friendly Bilateral Specialized Company (BSCO) plasters could have comparable mechanical properties to traditional plasters. Additionally, it is suggested that eco-friendly and carbon-free plasters can be a viable alternative to traditional plasters in a variety of applications. Researchers and civil engineers can both gain from this scientific paper’s potential to replace conventional stucco with an ecologically friendly alternative that has more effective mechanical qualities.