bluuebunny/crossref_metadata_2025 huggingface dataset:
META-GLARE: A Computer-Interpretable Guideline System Shell
Authors: Bottrighi Alessio , Terenziani Paolo
Published: July 2023

Computer-interpretable Guideline (CIG) systems are important tools for ensuring healthcare practice quality and standardization. They usually provide a tool to acquire CIGs, and one to execute them on specific patients. Current CIG systems rely on their own formalism to represent clinical guidelines, so moving to new phenomena/domains may require substantial extensions. We propose an innovative approach, providing a “shell” that facilitates system designers to define new CIG systems (or to update an existing one) through the definition of a new CIG representation formalism, based on the Task-Network model. We based it on our previous work on META-GLARE, and we extend it with a general execution tool, able to operate on any CIG representation formalism acquired through the META-GLARE acquisition tool. Developed with modularity and compositionality principles, the tool exploits an open library of basic execution methods. It offers a general execution mechanism supporting various CIG formalisms. We successfully applied our approach to three practical case studies. We have identified a reference CIG formalism (the one currently supported by the META-GLARE library) and compared its expressiveness to benchmark approaches. META-GLARE constitutes the first shell in the literature to facilitate the (formalism-based) design and development of CIG systems, considering both acquisition and execution.
Investigating the Spread of Antimicrobial Drug-Resistant Microorganisms in Dairy Sheep Farms: A Follow-Up Study
Authors: Mataragka Antonia , Tzimotoudis Nikolaos , Mavrommatis Alexandros , Tsiplakou Eleni , Symeonidou Andrianna , Kotsikori Maria , Zervas George , Ikonomopoulos John
Published: July 2023

Recently, we investigated the spread of antimicrobial drug-resistant (AMR) microorganisms in five dairy sheep farms in Greece to identify indicators for improved field surveillance. The high percentage of samples of feeds and milk positive to Escherichia coli and Staphylococci, including AMR isolates, recorded in this previous study generated the interest to further investigate the parameters likely to affect positivity of these certain indicators in the same farms. For this reason, 76 samples were collected, comprising milk collected from the raw milk tank (n = 5), swabs from milking shells (n = 48), feeds (n = 6), and home-grown feeds (n = 17). Samples were processed for the detection of the pathogens mentioned above and the assessment of AMR using conventional microbiology and the polymerase chain reaction. The overall percentage of positive samples was 71.1%. The percentage of isolates that were characterised as AMR of those detected was 27.8% (30% Staphylococci, 21.4% E. coli). The results indicate that AMR testing in milking shell swabs is advisable for improving AMR stewardship and should be regarded as complimentary to testing samples from the raw milk tank, because these may not depict the microbial burden of milking shells. Furthermore, the spread and antimicrobial resistance of tested bacteria in feeds are characterised by considerable variability and should therefore be assessed longitudinally.
Investigating the Mediating Role of Pain in the Relationship between Ankle Joint Position Sense and Balance Assessed Using Computerized Posturography in Individuals with Unilateral Chronic Ankle Instability: A Cross-Sectional Study
Authors: Alfaya Fareed F. , Reddy Ravi Shankar , Alshahrani Mastour Saeed , Tedla Jaya Shanker , Dixit Snehil , Gular Kumar , Mukherjee Debjani
Published: July 2023

Chronic ankle instability (CAI) is characterized by impaired ankle joint position sense (JPS) and compromised balance. Despite previous studies investigating the correlation between ankle JPS and balance in individuals with CAI, the potential mediating effect of pain in this relationship remains unclear. Understanding the role of pain as a mediator between ankle JPS and balance could provide valuable insights into the complex interplay among these variables in individuals with CAI. Therefore, further research is needed to elucidate the mediating effect of pain and its implications in assessing and managing ankle JPS and balance deficits in individuals with CAI. This cross-sectional study aimed to investigate the mediating role of pain in the association between ankle JPS and balance in individuals with unilateral CAI. Methods: Fifty-five individuals diagnosed with CAI participated in this study. Ankle JPS was assessed using a digital inclinometer, whereas the balance was measured using a computerized dynamic posturography device. Results: Participants with CAI showed impaired ankle JPS in the affected leg compared to that in the asymptomatic leg (p < 0.001). Ankle JPS errors were greater in both dorsiflexion and plantarflexion directions in the CAI. Balance was compromised in the CAI leg (p < 0.001). Moderate correlations (p < 0.001, r = 0.31 to 0.48) were found between the balance variables. Pain significantly mediated the ankle JPS-balance relationship in the CAI (p < 0.05, Sobel test). The findings suggest that individuals with CAI exhibit impaired ankle JPS and compromised balance. Pain plays a mediating role in the association between ankle JPS and balance in individuals with CAI. These results highlight the importance of considering pain as a potential mediator when assessing and treating balance issues in individuals with CAI. Healthcare professionals should incorporate assessments of ankle JPS and pain into the management of interventions that address these factors and improve balance and functional ability.
Application of Machine Learning Ensemble Methods to ASTRI Mini-Array Cherenkov Event Reconstruction
Authors: Pagliaro Antonio , Cusumano Giancarlo , La Barbera Antonino La , La Parola Valentina La , Lombardi Saverio
Published: July 2023

The Imaging Atmospheric Cherenkov technique has opened up previously unexplored windows for the study of astrophysical radiation sources in the very high-energy (VHE) regime and is playing an important role in the discovery and characterization of VHE gamma-ray emitters. However, even for the most powerful sources, the data collected by Imaging Atmospheric Cherenkov Telescopes (IACTs) are heavily dominated by the overwhelming background due to cosmic-ray nuclei and cosmic-ray electrons. As a result, the analysis of IACT data necessitates the use of a highly efficient background rejection technique capable of distinguishing a gamma-ray induced signal through identification of shape features in its image. We present a detailed case study of gamma/hadron separation and energy reconstruction. Using a set of simulated data based on the ASTRI Mini-Array Cherenkov telescopes, we have assessed and compared a number of supervised Machine Learning methods, including the Random Forest method, Extra Trees method, and Extreme Gradient Boosting (XGB). To determine the optimal weighting for each method in the ensemble, we conducted extensive experiments involving multiple trials and cross-validation tests. As a result of this thorough investigation, we found that the most sensitive Machine Learning technique applied to our data sample for gamma/hadron segregation is a Stacking Ensemble Method composed of 42% Extra Trees, 28% Random Forest, and 30% XGB. In addition, the best-performing technique for energy estimation is a different Stacking Ensemble Method composed of 45% XGB, 27.5% Extra Trees, and 27.5% Random Forest. These optimal weightings were derived from extensive testing and fine-tuning, ensuring maximum performance for both gamma/hadron separation and energy estimation.
Research on Fidelity Performance of Coring Bits during Drilling and Cutting in Deep Extreme Environments
Authors: Sun Fuda , Chen Ling , Li Yanyan , Wang Zhehao , Xiao Bin , Chen Zexiang
Published: July 2023

Deep rock formations in extreme environments are characterized by complex working conditions, various structures, high hardness, and high resistance to compression. However, existing coring techniques leave the cores of deep rock formations vulnerable to residual stresses, resulting in poor fidelity during deep coring. This paper develops a rock-breaking model for the structural parameters of drill bits. It proposes that a drill bit’s structural parameters in terms of back-rake and side-rake angles will affect the core’s fidelity performance. In addition, the core’s mechanical specific energy and maximum stress will reflect the fidelity effect. The accuracy of the theoretical model was verified via simulation analysis. The simulation results show that the tool’s average cutting force and Standard deviation of cutting force increase as the drill bit’s back-rake and side-rake angles vary. This leads to increased shear friction on the core, which affects the maximum stress and mechanical specific energy, and, subsequently, the fidelity of the core. The back-rake angles ranged from 15° to 25°, with the optimum back-rake angle of 21° producing a maximum stress and a mechanical specific energy that were 0.69 and 0.85 times higher than the highest point, respectively. The side-rake angles range from 5° to 15°, with the optimum side-rake angle of 10° producing a maximum stress and a mechanical specific energy that were 0.76 and 0.96 times higher than the highest point, respectively. The finite element method error was 1.21%. This work’s main results will help reveal the fidelity mechanisms of the drilling process and contribute to the development of fidelity drill bits for complex surface drilling processes.
Dynamic Obstacle Avoidance and Path Planning through Reinforcement Learning
Authors: Almazrouei Khawla , Kamel Ibrahim , Rabie Tamer
Published: July 2023

The use of reinforcement learning (RL) for dynamic obstacle avoidance (DOA) algorithms and path planning (PP) has become increasingly popular in recent years. Despite the importance of RL in this growing technological era, few studies have systematically reviewed this research concept. Therefore, this study provides a comprehensive review of the literature on dynamic reinforcement learning-based path planning and obstacle avoidance. Furthermore, this research reviews publications from the last 5 years (2018–2022) to include 34 studies to evaluate the latest trends in autonomous mobile robot development with RL. In the end, this review shed light on dynamic obstacle avoidance in reinforcement learning. Likewise, the propagation model and performance evaluation metrics and approaches that have been employed in previous research were synthesized by this study. Ultimately, this article’s major objective is to aid scholars in their understanding of the present and future applications of deep reinforcement learning for dynamic obstacle avoidance.
Improved YOLOv4-tiny Target Detection Method Based on Adaptive Self-Order Piecewise Enhancement and Multiscale Feature Optimization
Authors: Cai Dengsheng , Lu Zhigang , Fan Xiangsuo , Ding Wentao , Li Bing
Published: July 2023

To improve the accuracy of material identification under low contrast conditions, this paper proposes an improved YOLOv4-tiny target detection method based on an adaptive self-order piecewise enhancement and multiscale feature optimization. The model first constructs an adaptive self-rank piecewise enhancement algorithm to enhance low-contrast images and then considers the fast detection ability of the YOLOv4-tiny network. To make the detection network have a higher accuracy, this paper adds an SE channel attention mechanism and an SPP module to this lightweight backbone network to increase the receptive field of the model and enrich the expression ability of the feature map. The network can pay more attention to salient information, suppress edge information, and effectively improve the training accuracy of the model. At the same time, to better fuse the features of different scales, the FPN multiscale feature fusion structure is redesigned to strengthen the fusion of semantic information at all levels of the network, enhance the ability of network feature extraction, and improve the overall detection accuracy of the model. The experimental results show that compared with the mainstream network framework, the improved YOLOv4-tiny network in this paper effectively improves the running speed and target detection accuracy of the model, and its mAP index reaches 98.85%, achieving better detection results.
Global Dynamics of a Predator–Prey System with Cooperative Hunting
Authors: Bai Dingyong , Tang Jiaoxin
Published: July 2023

We consider a predator–prey system with cooperative hunting. The parameter space of the system is divided into several mutually exclusive regions. Based on the investigation of the dynamical properties in each parameter region, we provide a complete description of the global dynamics, including stability, Hopf bifurcation and its directions, and the existence of limit cycles. By comparing this system’s dynamics to those of a system without cooperative hunting, it is found that cooperative hunting is beneficial to the coexistence of the prey and predator. When the mortality of the predator is small, hunting cooperation does not affect the coexistence of populations but it affects the pattern of coexistence.
Preliminary Investigation on Steel Jacketing Retrofitting of Concrete Bridges Half-Joints
Authors: Bertagnoli Gabriele , Ferrara Mario , Giordano Luca , Malavisi Marzia
Published: July 2023

An innovative strengthening system for dapped-end beams is studied numerically and experimentally in this paper. The system is developed for the half-joint regions of bridge beams also commonly called “gerber saddles”, but it can be adapted to different scenarios. The strengthening system consists of two steel plates that are clamped on both sides of the webs of the beams by means of bolts. The purpose of the system is to transfer the highest possible amount of shear from the concrete webs to the steel plate elements reducing the resistance demand of the concrete half joint. Shear is transferred by friction from concrete to steel plates. The system is designed to be applied on existing bridges without heavy work interesting the carriageway, therefore reducing the interference with the traffic. Some interesting considerations emerge from the study, including the influence of the flange web connection on the structural behavior and the possible presence of brittle failure mechanisms that are difficult to model numerically using f.e.m. simulations.
Influence of Addition of Dried Maitake and Enoki Mushrooms on Antioxidant, Potentially Anti-Inflammatory, and Anti-Cancer Properties of Enriched Pasta
Authors: Szydłowska-Tutaj Magdalena , Szymanowska Urszula , Tutaj Krzysztof , Domagała Dorota , Złotek Urszula
Published: July 2023

The influence of the addition of 2.5, 5, 7.5, and 10.0% of dried Enoki and Maitake mushrooms on the content of bioactive compounds and some nutraceutical properties of pasta was determined in the study. The LC-MS/MS analysis of phenolic compounds revealed the highest amount of phenolic compounds in the Maitake-supplemented pasta. However, all the samples of the Enoki-enriched pasta exhibited a statistically significantly higher content of α-glucans than the control. Samples subjected to gastrointestinal digestion had significantly higher antioxidant and potential anti-inflammatory activities than ethanolic and buffer extracts (PBS). The ethanolic extracts from the Enoki- and Maitake-supplemented pasta had higher antioxidant activity (in some antiradical and reducing power assays) and higher lipoxygenase (E2.5 and E5 samples) inhibitory potential compared to the control sample. Additionally, some in vitro digested samples of pasta enriched with dried Enoki and Maitake mushrooms showed higher chelating power (E10, M7.5, and M10), reducing power (E5, E7.5, and M10), and lipoxygenase inhibition ability (E7.5, E10, and M10) than the control. In conclusion, the fortification of pasta with 7.5% and 10% of Enoki mushrooms and with 10% of Maitake mushrooms can be recommended.
Research on the Influence of Exoskeletons on Human Characteristics by Modeling and Simulation Using the AnyBody Modeling System
Authors: Cao Lin , Zhang Junxia , Zhang Peng , Fang Delei
Published: July 2023

Lower limb-powered exoskeletons can help rehabilitate patients with lower limb disabilities. However, the changes in the biomechanical load on the human body when exoskeletons are used are still poorly understood. The goal of this study was to investigate the changes in kinematic and biomechanical parameters of the lower extremity exoskeleton when worn by normal subjects and patients with unilateral motor impairment using a virtual prototype. The effect of wearing the exoskeleton on gait was derived, and the basis for exoskeleton optimization was given. Virtual prototyping is a cost-effective method to validate the performance of exoskeleton robots. Therefore, two models, a human-exoskeleton model and an asymmetric movement disorder (SSP) subject-exoskeleton model, were developed in AnyBody software for this study. The human-exoskeleton model was driven by the kinematic data of 20 healthy participants walking in an exoskeleton at normal speed (3.6 km/h). As a comparison, the SSP subject-exoskeleton model was driven by data from five SSP subjects walking in an exoskeleton. The experimental results show that after wearing the lower limb exoskeleton, the walking gait satisfies the normal human gait characteristics, but some of the muscle forces suddenly increase. The maximum activation level does not exceed 1, which means that the exoskeleton does not cause muscle damage or fatigue in a short period of time. In both models, the vertical ground reaction force (GRF) Z correlation was the strongest (R > 0.90). The center of pressure (COP) X trajectory correlation was the weakest (R < 0.35). These findings will support the study of the effects of exoskeletal optimization. Also, some gait characteristics of exoskeletons worn by patients with unilateral dyskinesia can be initially explored.
Metrics Related to Confusion Matrix as Tools for Conformity Assessment Decisions
Authors: Božić Dubravka , Runje Biserka , Lisjak Dragutin , Kolar Davor
Published: July 2023

Conformity assessment refers to activities undertaken to check whether some product, service or process meets certain criteria and specifications given by internationally accepted standards. The decision on whether a property of interest is aligned with the set standards is made based on measurement. However, uncertainty associated with the measurement results may lead to incorrect decisions. Measurement results may be falsely rejected as non-conforming, although they meet specifications. This is referred to as the producer’s risk. If the measurement result that does not meet the required specifications is accepted as conforming, this is referred to as the consumer’s risk. This paper covers calculations of global consumer's and producer's risk using the Bayesian approach and deals with the application of metrics related to confusion matrices in conformity assessments. These techniques have been used to assess the conformity of the bearing ring diameter with the given specifications. Based on the behavior of these metrics, the optimal length of the guard band was determined with the aim of minimizing the global consumer’s and producer’s risk.
Experimental Study on the Risk Preference Characteristics of Members in Supply Chain Emergencies
Authors: Gu Yulei , Chen Wenqiang , Liu Haiping
Published: July 2023

Since risk preference affects the behavior of decision makers, the study of its characteristics and impact on decision-making contributes to good planning for emergency coordination. The consistency of a member’s risk preferences in the conventional risk field and emergencies of a supply chain was analyzed by applying the prospect theory and adapting the domain-specific risk-taking (DOSPERT) scale. The influence of time pressure on the risk preferences and decision-making behaviors of members was studied in the emergency field and its sub-emergencies of a supply chain. The conclusions were drawn based on the empirical study. First, the risk preference could be measured in terms of conventional risk and emergencies. Second, the members tended to be risk averse with no time pressure, and the degree of risk aversion was weakened with time pressure, which had the greatest effect in the natural disaster event. Third, even though the change in risk preference had a consistency regarding the four types of sub-events of supply chain emergencies, it was inconsistent regarding the conventional risks and emergencies. With the evolution trend of risk preference demonstrated and the relationship between preference and time pressure revealed, this study may provide a decision-making reference for the formulation of a supply chain emergency coordination scheme.
On the Development of an Intelligent Poly(aniline-co-o-toluidine)/Fe3O4/Alkyd Coating for Corrosion Protection in Carbon Steel
Authors: Mousa Oday I. , Al-Luaibi Salah S. , Al-Mubarak Alaa S. , Lgaz Hassane , Hammouti Belkheir , Chaouiki Abdelkarim , Ko Young Gun
Published: July 2023

The corrosion of metals and alloys presents a significant challenge in many industries, demanding constant maintenance, and thereby increasing costs. In response to this problem, the smart corrosion protection coating has emerged as a promising solution. By enabling the immediate detection of, and response to, environmental changes, such as in the temperature and pH, these smart coatings contribute significantly to extending a material’s lifespan, and reducing maintenance expenses. In this study, nanomagnetic [poly(aniline-co-o-toluidine)/Fe3O4] systems were prepared and used as a self-healing corrosion inhibitor, mixed with alkyd paint at different weight percentages (5–25%). The composites were used as a coating on carbon steel (C1010), and their corrosion protection performance was tested in 0.1 mol/L HCl, using electrochemical impedance spectroscopy (EIS), scanning electron microscope (SEM), and FTIR analyses. The results showed an adequate corrosion inhibition performance for the developed composites, compared to the alkyd paint alone, reaching an inhibition efficiency of 80% at 20 wt.% of composite. Adding increasing weight percentages of the developed composites to the paints led to a significant increase in the corrosion resistance, accompanied by a remarkable decrease in the double-layer capacitance. Thus, these developed composites show excellent potential as a corrosion protection formulation in paints.
OneBitPitch (OBP): Ultra-High-Speed Pitch Detection Algorithm Based on One-Bit Quantization and Modified Autocorrelation
Authors: Coccoluto Davide , Cesarini Valerio , Costantini Giovanni
Published: July 2023

This paper presents a novel, high-speed, and low-complexity algorithm for pitch (F0) detection, along with a new dataset for testing and a comparison of some of the most effective existing techniques. The algorithm, called OneBitPitch (OBP), is based on a modified autocorrelation function applied to a single-bit signal for fast computation. The focus is explicitly on speed for real-time pitch detection applications in pitch detection. A testing procedure is proposed using a proprietary synthetic dataset (SYNTHPITCH) against three of the most widely used algorithms: YIN, SWIPE (Sawtooth Inspired Pitch Estimator) and NLS (Nonlinear-Least Squares-based). The results show how OBP is 9 times faster than the fastest of its alternatives, and 50 times faster than a gold standard like SWIPE, with a mean elapsed time of 4.6 ms, or 0.046 × realtime. OBP is slightly less accurate for high-precision landmarks and noisy signals, but its performance in terms of acceptable error (<2%) is comparable to YIN and SWIPE. NLS emerges as the most accurate, but it is not flexible, being dependent on the input and requiring prior setup. OBP shows to be robust to octave errors while providing acceptable accuracies at ultra-high speeds, with a building nature suited for FPGA (Field-Programmable Gate Array) implementations.
Numerical Assessment of the Seismic Vulnerability of Bridges within the Italian Road Network
Authors: Furinghetti Marco , Reale Simone , Fox Matthew J. , Pavese Alberto
Published: July 2023

The safety of existing bridges represents a serious problem in Italy since these structures are fundamental for the national transportation system and, at the same time, can be subject to significant deterioration phenomena linked to the fact that the construction period typically dates back to the 1960s. This study involves the seismic analysis of five case study bridges belonging to the Italian Road Network. Using nonlinear time–history analysis with sets of code-spectrum compatible ground motions, analytical fragility curves have been constructed for each of the five bridges. The results obtained interpreting the analytical fragility curves agree with the fact that the seismic behavior of existing bridges can be problematic and that higher seismicity can be associated with more detrimental behavior. In particular, the results reveal that in regions with higher seismicity, the main problems in bridges are related to bearings and connecting elements located in the piers. Five case studies have also been analyzed to determine the Structural and Foundational Class of Attention and Seismic Class of Attention, following the approach proposed by the 2020 Italian Guidelines. In this way, it is possible to compare two different assessment approaches with different safety levels. The results obtained with the two approaches are in good agreement considering bridges in high seismicity regions, while the procedure of the Guidelines could lead to not reflecting the seismic behavior of bridges when the seismicity of the area is lower.
Experimental Analysis of a Spray Hydrocooler with Cold Energy Storage for Litchi
Authors: Huang Hao , Lv Enli , Lu Huazhong , Guo Jiaming
Published: July 2023

The shortage of precooling equipment in litchi-producing regions could lead to a high loss rate and poor quality of litchis. It is urgent to develop a portable precooling device for litchi-producing regions. In this study, a novel spray hydrocooler with thermal energy storage (TES) was designed, fabricated, and tested. A simple mathematical model of TES capacity, the ice-on-coil thermal resistance, and refrigeration system was employed to determine the hydrocooler parameters. Then, the structure of the spray hydrocooler was designed. The maximum charging test was implemented with full TES capacity, and the litchi spray hydrocooling experiments were carried out at different charging times (3–6 h), spray flow rates (30–60 L min−1), and litchi loads (8–28 kg) with one-third TES capacity. Results showed that: (1) the spray hydrocooler allows for the rapid and effective precooling of litchis within 15 min after harvest; (2) the hydrocooler can precool 299 kg litchis with one-third TES storage, meeting the precooling requirements; (3) the effective TES capacity achieved 1.25 × 108 J at the maximum TES capacity of the hydrocooler, while the energy efficiency ratio (EER) is 2; (4) the precooling capacity was maximum and the average power consumption was minimum when the litchi load was 23 kg and the spray flow rate was 30 L min−1. Longer charging time is the most important factor in increasing the precooling capacity and reducing the average power consumption. It provides feasible precooling equipment for rapid precooling in litchi-production regions.
Mechanical Performance Analysis and Experimental Study of Four-Star-Type Crank-Linkage Mechanism
Authors: Chai Kai , Lou Jingjun , Yang Yunsheng
Published: July 2023

Mechanical performance analysis and experimental study of the mechanics of the four-star-type crank-linkage mechanism of the marine air compressor were carried out to improve the submerged floating performance and stealth performance of the underwater vehicle and to meet the demand of its large diving depth. Firstly, we analyzed the forces on the four-star-type crank-linkage mechanism, derived the inertia forces and moments of the crank-linkage mechanism, and proved the advantages of the four-star-type crank-linkage mechanism in balancing the second-order reciprocating inertia forces. The static strength of some parts was calibrated, and the modal analysis of the four-star-type crank-linkage mechanism was carried out. Second, a flexible crankshaft dynamics model was established to study the influence of kinematic pair parameters on the excitation characteristics of the main bearing. The mechanical performance analysis of the mechanics of the four-star-type crank-linkage with clearance was carried out. Finally, a test bench of four-star-type crank-linkage mechanism was designed and built independently to analyze the effects of clearance size and rotational speed on the acceleration of the motion and vibration acceleration of the slider. The results show that the first-order reciprocating inertia force and second-order reciprocating moment of inertia mainly exist in the four-star-type crank-linkage mechanism. The friction force of the revolving pair can suppress part of the resonance peak, but it will broaden the excitation band and excite high-frequency vibration. The larger the clearance of the four-star-type crank-linkage mechanism kinematic pair, the higher the crankshaft speed, the larger the acceleration amplitude, and the more concentrated the phase trajectory. The research results of this paper can guide the low-noise design of other types of air compressors, help to improve the overall level of marine air compressors, and show future directions for the vibration control of four-star-type air compressors.
Shear Transfer Resistance with Different Interface Conditions: Evaluation of Design Provisions and Proposed Equation
Authors: Diep Hung Thanh , Choi Byung H.
Published: July 2023

The design provisions in current codes for shear resistance of concrete-to-concrete interfaces exhibit significant differences. In this study, the accuracy of design provisions for interface shear resistance was evaluated and compared. From the literature search, a database of 458 push-off test results of interface shear resistance was created to evaluate the shear transfer provisions from the ACI 318-19, PCI Design Handbook, AASHTO LRFD Bridge Design Specifications, CSA-S6, Eurocode 2, and Fib Model Code 2010. In addition, an equation was derived based on push-off test results collected from the literature to calculate the interface shear resistance for the monolithic uncracked interface. According to many analyses and evaluations of parameters affecting the interface shear resistance, the compressive strength of concrete played an important role, especially for the monolithic uncracked interface. Therefore, the compressive strength of concrete was included in the proposed equation to calculate the interface shear resistance in this study. It is expected that this equation can be applied more accurately than the existing design provisions when high-strength concrete is used. Statistical analyses were carried out for comparison with the existing design provisions to verify the applicability of the proposed equation. The results show that the proposed equation reasonably predicted the interface shear resistance for the monolithic uncracked interface. Appropriate conclusions were also drawn for the design provisions.
Designing Bio-Based Color Sensor from Myofibrillar-Protein-Based Edible Film Incorporated with Sappan Wood (Caesalpinia sappan L.) Extract for Smart Food Packaging
Authors: Rostini Iis , Junianto  , Warsiki Endang
Published: July 2023

The use of intelligent sensor-based packaging in food products allows the quick evaluation of food quality. This study aimed to design a color sensor from surimi utilizing sappan wood extract (SWE) for intelligent food packaging. The myofibrillar-protein-based edible film incorporated the SWE at different concentrations (0.15%, 0.25%, and 0.35%). The physical properties of the sappan wood–surimi edible film (SSEF) were analyzed, and the color changes at various pH levels and soaking times under different conditions were assessed. According to the results, different concentrations of the SWE significantly affected the thickness, transparency, tensile strength, and elongation at break of the film. However, the values were still within the acceptable range. The pH values increased the film’s darkness, redness, and blueness. Based on the evaluation of the SSEF under different soaking conditions, the color changes of the film in acidic conditions were more stable than in neutral and alkaline conditions. This study showed that SSEF can be used as intelligent food packaging. It can act as a color sensor due to its sensitivity to the changes in the pH condition of the product.
Passive-Tuned Mass Dampers for the Pointing Accuracy Mitigation of VLBI Earth-Based Antennae Subject to Aerodynamic Gust
Authors: Gasparetto Victor E. L. , Reid Jackson , ElSayed Mostafa S. A.
Published: July 2023

This paper proposes an optimization procedure to achieve the best configuration of multiple degrees of freedom Tuned Mass Dampers (TMDs) to mitigate the pointing error of Very-Long-Baseline Interferometry (VLBI) Earth-based radio antennae operating under aerodynamic gust conditions. In order to determine the optimum sets of TMDs, a Multi-Objective design optimization employing a genetic algorithm is implemented. A case study is presented where fourteen operational scenarios of wind gust are considered, employing two models of atmospheric disturbances, namely the Power Spectral Density (PSD) function with a statistical profile presented by the Davenport Spectrum (DS) and a Tuned Discrete Gust (TDG) modeled as a one-minus cosine signal. It is found that the optimal configurations of TMDs are capable of reducing the pointing error of the antenna by an average of 66% and 50% for the PSD and TDG gust excitation scenarios, respectively, with a mass inclusion of 1% of the total mass of the antenna structure. The optimal TMD parameters determined herein can be utilized for design and field implementation in antenna systems, such that their structural efficiency can be enhanced for radio astronomy applications.
Perspectives on Using a Competitive Exclusion Approach to Control Listeria monocytogenes in Biological Soil Amendments of Animal Origin (BSAAO): A Review
Authors: Wang Hongye , Huang Jinge , Jiang Xiuping
Published: July 2023

Biological soil amendments of animal origin (BSAAO), such as animal waste or animal-waste-based composts, may contain foodborne pathogens such as Listeria monocytogenes. Due to the ubiquitous nature of Listeria, it is essential to understand the behavior of L. monocytogenes in BSAAO in order to develop preharvest prevention strategies to reduce pathogen contamination. As biological control agents, competitive exclusion (CE) microorganisms have been widely utilized in agriculture to control plant- or foodborne pathogens. Due to the diverse microbial community, animal wastes and composts are the potential sources for isolating CE strains for pathogen control. To explore the potential of using CE to control L. monocytogenes in BSAAO, we thoroughly reviewed the studies on the fate of L. monocytogenes in the agriculture field, and in the isolation and identification of CE from different matrices, and the applications of CE as a biological control method. Future studies using a next-generation sequencing approach to identify and characterize CE strains in complex microbial communities can provide a comprehensive picture of the microbial interactions between invading pathogens and the indigenous microbiota in BSAAO. This comprehensive review will provide insight into the development of effective biological control measures for preventing L. monocytogenes contamination in the agricultural field and enhancing food safety.
Feel the Music!—Audience Experiences of Audio–Tactile Feedback in a Novel Virtual Reality Volumetric Music Video
Authors: Young Gareth W. , O’Dwyer Néill , Vargas Mauricio Flores , Donnell Rachel Mc , Smolic Aljosa
Published: July 2023

The creation of imaginary worlds has been the focus of philosophical discourse and artistic practice for millennia. Humans have long evolved to use media and imagination to express their inner worlds outwardly via artistic practice. As a fundamental factor of fantasy world-building, the imagination can produce novel objects, virtual sensations, and unique stories related to previously unlived experiences. The expression of the imagination often takes a narrative form that applies some medium to facilitate communication, for example, books, statues, music, or paintings. These virtual realities are expressed and communicated via multiple multimedia immersive technologies, stimulating modern audiences via their combined Aristotelian senses. Incorporating interactive graphic, auditory, and haptic narrative elements in extended reality (XR) permits artists to express their imaginative intentions with visceral accuracy. However, these technologies are constantly in flux, and the precise role of multimodality has yet to be fully explored. Thus, this contribution to Feeling the Future—Haptic Audio explores the potential of novel multimodal technology to communicate artistic expression via an immersive virtual reality (VR) volumetric music video. We compare user experiences of our affordable volumetric video (VV) production to more expensive commercial VR music videos. Our research also inspects audio–tactile interactions in the auditory experience of immersive music videos, where both auditory and haptic channels receive vibrations during the imaginative virtual performance. This multimodal interaction is then analyzed from the audience’s perspective to capture the user’s experiences and examine the impact of this form of haptic feedback in practice via applied human–computer interaction (HCI) evaluation practices. Our results demonstrate the application of haptics in contemporary music consumption practices, discussing how they affect audience experiences regarding functionality, usability, and the perceived quality of a musical performance.
Quantifying Raindrop Evaporation Deficit in General Circulation Models from Observed and Model Rain Isotope Ratios on the West Coast of India
Authors: Sengupta Saikat , Bhattacharya Sourendra Kumar , Sunil Nimya Sheena , Sonar Sumit
Published: July 2023

Raindrop evaporation is an important sub-cloud process that modifies rainfall amount and rainwater isotope values. Earlier studies have shown that various general circulation models (GCMs) do not incorporate this process properly during the simulation of water isotope ratios (oxygen and hydrogen). Our recent study has demonstrated that an inadequate estimation of this process for the Indian Summer Monsoon (ISM) results in significant biases (model-observed values) in the simulation of various GCMs on a monthly scale. However, a quantitative estimation was lacking. The magnitude of raindrop evaporation depends upon ambient humidity and temperature, which vary considerably during the ISM. Consequently, the isotope biases would also vary over various time scales. The present study aims to investigate the magnitude of the monthly scale variation in raindrop evaporation in the simulations and its causal connection with the corresponding variation in isotope biases. Towards this, we compare an 11-year-long (1997–2007) dataset of rain isotope ratios (both oxygen and hydrogen) from an Indian station, Kozhikode (Kerala), obtained under the Global Network of Isotopes in Precipitation (GNIP) programme of the International Atomic Energy Agency (IAEA) with the corresponding outputs of two isotope-enabled nudged GCMs—ISOGSM and LMDZ4. The raindrop evaporation fractions are estimated for 44 ISM months (June–September) of the study period using the Stewart (1975) formalism. Using a simple condensation–accretion model based on equilibrium fractionation from vapour, obtained from two adopted vapour isotope profiles, we estimate the liquid water isotope ratios at the cloud base. Considering this water as the initial rain, the raindrop evaporation fractions are estimated using the observed oxygen and hydrogen isotope ratios of Kozhikode surface rain samples. The estimated fractions show strong positive correlations with the isotope biases (R2 = 0.60 and 0.66). This suggests that lower estimates of raindrop evaporation could be responsible for the rain isotope biases in these two GCMs.
Quantum Circuit Template Matching Optimization Method for Constrained Connectivity
Authors: Gao Xiaofeng , Guan Zhijin , Feng Shiguang , Jiang Yibo
Published: July 2023

The execution of quantum algorithms requires two key considerations. On the one hand, it should meet the connectivity constraint requirements of quantum circuit mapping for quantum architectures, and on the other hand, it needs to consider reducing the probability of errors in the execution of quantum circuits as much as possible. This paper proposes a novel optimization technique based on template matching that to satisfy both requirements. The template matching optimization method can significantly reduce the number of gates in a quantum circuit and further enhance its practicality. It stands as advanced optimization technology available today. Our method optimizes quantum logic circuits mapped onto quantum architecture by initially selecting their linear substructure. We then zone the circuit according to the gate dependency graph and optimize each block through template matching. Finally, we reorganize the circuit to obtain the optimized version as the final result. Our proposed method is amenable to various quantum architectures. To evaluate its efficacy, we conduct a comparative analysis with the t|ket⟩ and Qiskit compiler using a set of benchmark test circuits. Specifically, compare to the t|ket⟩ compiler method, the highest average optimization rate of our method can reach 25.75%. Compare with the Qiskit compiler method, the highest average optimization rate can reach 32.72%. Overall, our approach has significant optimization advantages.
An Unscented Kalman Filter-Based Robust State of Health Prediction Technique for Lithium Ion Batteries
Authors: Ranga MadhuSudana Rao , Aduru Veera Reddy , Krishna N. Vamsi , Rao K. Dhananjay , Dawn Subhojit , Alsaif Faisal , Alsulamy Sager , Ustun Taha Selim
Published: July 2023

Electric vehicles (EVs) have emerged as a promising solution for sustainable transportation. The high energy density, long cycle life, and low self-discharge rate of lithium-ion batteries make them an ideal choice for EVs. Recently, these batteries have been prone to faster decay in life span, leading to sudden failure of the battery. To avoid uncertainty among EV users with sudden battery failures, a robust health monitoring and prediction scheme is required for the EV battery management system. In this regard, the Unscented Kalman Filter (UKF)-based technique has been developed for accurate and reliable prediction of battery health status. The UKF approximates nonlinearity using a set of sigma points and propagates them via the nonlinear function to enhance battery health estimation accuracy. Furthermore, the UKF-based health estimation scheme considers the state of charge (SOC) and internal resistance of the battery. Here, the UKF-based health prediction technique is compared with the Extended Kalman filter (EKF) scheme. The robustness of the UKF and EKF-based health prognostic techniques were studied under varying initial SOC values. Under these abrupt changing conditions, the proposed UKF technique performed effectively in terms of state of health (SOH) prediction. Accurate SOH determination can help EV users to decide when the battery needs to be replaced or if adjustments need to be made to extend its life. Ultimately, accurate and reliable battery health estimation is essential in vehicular applications and plays a pivotal role in ensuring lithium-ion battery sustainability and minimizing environmental impacts.
Experimental Investigation on the Thermal Management for Lithium-Ion Batteries Based on the Novel Flame Retardant Composite Phase Change Materials
Authors: Yu Yue , Zhang Jiaxin , Zhu Minghao , Zhao Luyao , Chen Yin , Chen Mingyi
Published: July 2023

Thermal management systems are critical to the maintenance of lithium-ion battery performance in new energy vehicles. While phase change materials are frequently employed in battery thermal management systems, it’s important to address the concerns related to their leakage and flammability, as they can pose hazards to the safety performance of batteries. This paper proposes a novel flame retardant composite phase change material (CPCM) consisting of paraffin, high-density polyethylene, expanded graphite, ammonium polyphosphate, red phosphorus, and zinc oxide. The performance of CPCMs containing different ratios of flame retardants is investigated, and their effects when applied to battery thermal management systems are compared. The results demonstrate that the leakage rate of the flame retardant CPCMs is maintained within 1%, indicating excellent flame retardant performance and thermal management efficiency. The combination of ammonium polyphosphate and red phosphorus in the flame retardant exhibits effective synergistic effects, while zinc oxide may help phosphate compounds create their bridging bonds, which would then make it possible to construct a char layer that would separate heat and oxygen. Under a 2C discharge rate, the maximum temperature of the battery pack remains below 50 °C, and the temperature difference can be controlled within 5 °C. Even under a 3C discharge rate, the maximum temperature and temperature difference are reduced by 30.31% and 29.53%, respectively.
A Semi-Three-Dimensional Bioprinted Neurocardiac System for Tissue Engineering of a Cardiac Autonomic Nervous System Model
Authors: Hernandez Ivana , Ramirez Salma P. , Salazar Wendy V. , Mendivil Sarahi , Guevara Andrea , Patel Akshay , Loyola Carla D. , Dorado Zayra N. , Joddar Binata
Published: July 2023

In this study, we designed a tissue-engineered neurocardiac model to help us examine the role of neuronal regulation and confirm the importance of neural innervation techniques for the regeneration of cardiac tissue. A three-dimensional (3D) bioprinted neurocardiac scaffold composed of a mixture of gelatin–alginate and alginate–genipin–fibrin hydrogels was developed with a 2:1 ratio of AC16 cardiomyocytes (CMs) and retinoic acid-differentiated SH-SY5Y neuronal cells (NCs) respectively. A unique semi-3D bioprinting approach was adopted, where the CMs were mixed in the cardiac bioink and printed using an anisotropic accordion design to mimic the physiological tissue architecture in vivo. The voids in this 3D structure were methodically filled in using a NC–gel mixture and crosslinked. Confocal fluorescent imaging using microtubule-associated protein 2 (MAP-2) and anticholine acetyltransferase (CHAT) antibodies for labeling the NCs and the MyoD1 antibody for the CMs revealed functional coupling between the two cell types in the final crosslinked structure. These data confirmed the development of a relevant neurocardiac model that could be used to study neurocardiac modulation under physiological and pathological conditions.