bluuebunny/crossref_metadata_2025 huggingface dataset:
Optimal Navigation of an Unmanned Surface Vehicle and an Autonomous Underwater Vehicle Collaborating for Reliable Acoustic Communication with Collision Avoidance
Authors: Savkin Andrey , Verma Satish , Anstee Stuart
Published: January 2022

This paper focuses on safe navigation of an unmanned surface vehicle in proximity to a submerged autonomous underwater vehicle so as to maximise short-range, through-water data transmission while minimising the probability that the two vehicles will accidentally collide. A sliding mode navigation law is developed, and a rigorous proof of optimality of the proposed navigation law is presented. The developed navigation algorithm is relatively computationally simple and easily implementable in real time. Illustrative examples with extensive computer simulations demonstrate the effectiveness of the proposed method.
An Information Theoretic Interpretation to Deep Neural Networks
Authors: Xu Xiangxiang , Huang Shao-Lun , Zheng Lizhong , Wornell Gregory W.
Published: January 2022

With the unprecedented performance achieved by deep learning, it is commonly believed that deep neural networks (DNNs) attempt to extract informative features for learning tasks. To formalize this intuition, we apply the local information geometric analysis and establish an information-theoretic framework for feature selection, which demonstrates the information-theoretic optimality of DNN features. Moreover, we conduct a quantitative analysis to characterize the impact of network structure on the feature extraction process of DNNs. Our investigation naturally leads to a performance metric for evaluating the effectiveness of extracted features, called the H-score, which illustrates the connection between the practical training process of DNNs and the information-theoretic framework. Finally, we validate our theoretical results by experimental designs on synthesized data and the ImageNet dataset.
A Process Evaluation of a Learning Community Program: Implemented as Designed?
Authors: Lanphier Tonya Scott , Carini Robert M.
Published: January 2022

Learning communities can be useful to counter some of the challenges encountered by first-semester students as they transition to college. This 2-year process evaluation examines the launch of a campus-wide learning community initiative for developmental reading students at a community college in the USA. Students, instructors, and administrators were interviewed about the implementation of the program, and program-related materials were reviewed. Findings suggested ways to enhance the effectiveness of learning communities of the linked-course variety through program implementation that is more faithful to key design aspects. Suggestions include (1) implement team-teaching across linked courses; (2) carry out an integrated curriculum across courses; (3) provide in-depth and continued instructor training as well as specialized resources; (4) expand support services available to students and require them to use at least some; and (5) create tools/methods for instructors and administrators to regularly assess processual aspects rather than just program outcomes.
A Novel Power-Saving Reversing Camera System with Artificial Intelligence Object Detection
Authors: Hung Kuo-Ching , Lin Meng-Chun , Lin Sheng-Fuu
Published: January 2022

According to a study by the Insurance Institute for Highway Safety (IIHS), the driving collision rate of using only the reversing camera system is lower than that of using both the reversing camera system and the reversing radar. In this article, we implemented a reversing camera system with artificial intelligence object detection to increase the information of the reversing image. Our system consists of an image processing chip (IPC) with wide-angle image distortion correction and an image buffer controller, a low-power KL520 chip and an optimized artificial intelligence model MobileNetV2-YOLOV3-Optimized (MNYLO). The results of the experiment show the three advantages of our system. Firstly, through the image distortion correction of IPC, we can restore the distorted reversing image. Secondly, by using a public dataset and collected images of various weathers for artificial intelligence model training, our system does not need to use image algorithms that eliminate bad weathers such as rain, fog, and snow to restore polluted images. Objects can still be detected by our system in images contaminated by weather. Thirdly, compared with the AI model Tiny_YOLOV3, not only the parameters of our MNYLO have been reduced by 72.3%, the amount of calculation has been reduced by 86.4%, but the object detection rate has also been maintained and avoided sharp drops.
Geological and Engineering Integrated Shale Gas Sweet Spots Evaluation Based on Fuzzy Comprehensive Evaluation Method: A Case Study of Z Shale Gas Field HB Block
Authors: Liu Shiqi , Liu Yuyang , Zhang Xiaowei , Guo Wei , Kang Lixia , Yu Rongze , Sun Yuping
Published: January 2022

As an emerging unconventional energy resource, shale gas has great resource potential and developmental prospects. The effective evaluation of geological sweet spots (GSS), engineering sweet spots (ESS) and comprehensive sweet spots (CSS) is one of the main factors for a high-yield scale and economic production of shale gas. Sweet spot evaluation involves a comprehensive analysis based on multiple parameters. Conventional evaluation methods consider relatively simple or single factors. Although the main influencing factors are understood, the influence of different factors is as of yet unknown, and a comprehensive consideration may strongly affect the evaluation results. In this paper, the fuzzy mathematics method is introduced for shale gas sweet spot evaluation. With the help of fuzzy mathematics tools, such as membership function, the objective of comprehensive sweet spots evaluation based on multiple parameters is realized. Additionally, the reliability of the evaluation of sweet spots is improved. Firstly, previous research results are used for reference, and the evaluation factor system of geological and engineering sweet spots of shale gas is systematically analyzed and established. Then, the basic principle of the fuzzy comprehensive evaluation method is briefly introduced, and a geological engineering integrated shale gas sweet spots evaluation method, based on the fuzzy comprehensive evaluation method, is designed and implemented. Finally, the data from HB blocks in the Z shale gas field in China are adopted. According to the evaluation results, the modified method is tested. The results show that the method proposed in this paper can synthesize a number of evaluation indices, quickly and effectively evaluate the GSS, ESS and CSS in the target area, and the results have high rationality and accuracy, which can effectively assist in well-pattern deployment and fracture design.
Mathematical Model of Steam Reforming in the Anode Channel of a Molten Carbonate Fuel Cell
Authors: Szablowski Lukasz , Dybinski Olaf , Szczesniak Arkadiusz , Milewski Jaroslaw
Published: January 2022

The paper presents a mathematical model of a molten carbonate fuel cell with a catalyst in the anode channel. The modeled system is fueled by methane. The system includes a model of the steam reforming process occurring in the anode channel of the MCFC fuel cell and the model of the cell itself. A reduced order model was used to describe the operation of the molten carbonate fuel cell, whereas a kinetic model describes the methane steam reforming. The calculations of the reforming were done in Aspen HYSYS software. Four values of the steam-to-carbon ratio (2.0, 2.5, 3.0, and 3.5) were used to analyze the performance of the reforming process. In the first phase, the reaction kinetics model was based on data from the literature.
The Effects of Permanent Magnet Segmentations on Electromagnetic Performance in Ironless Brushless DC Motors
Authors: Zhai Fugang , Yang Liu , Fu Wenqi , Tong Haisheng , Zhao Tianyu
Published: January 2022

This paper investigates the electromagnetic torque by considering back electromagnetic force (back-EMF) trapezoidal degrees of ironless brushless DC (BLDC) motors through the two-dimensional finite element method (2-D FEM). First, the change percentages of the electromagnetic torque with back-EMF trapezoidal degrees, relative to those of PMs without segments, are investigated on the premise of the same back-EMF amplitude. It is found that both PM symmetrically and asymmetrically segmented types influence back-EMF trapezoidal degrees. Second, the corresponding electromagnetic torque, relative to that of PMs without segments, is studied in detail. The results show that the electromagnetic torque can be improved or deteriorated depending on whether the back-EMF trapezoidal degree is lower or higher than that of PMs without segments. Additionally, the electromagnetic torque can easily be improved by increasing the number of PMs’ symmetrical segments. In addition, the electromagnetic torque in PMs with asymmetrical segments is always higher than that of PMs without segments. Finally, two ironless PM BLDC motors with PMs symmetrically segmented into three segments and without segments are manufactured and tested. The experimental results show good agreement with those of the 2-D FEM method. This approach provides significant guidelines to electromagnetic torque improvement without much increase in manufacturing costs and process complexity.
Integrated Structural Dependence and Stochastic Dependence for Opportunistic Maintenance of Wind Turbines by Considering Carbon Emissions
Authors: Liu Qinming , Li Zhinan , Xia Tangbin , Hsieh Minchih , Li Jiaxiang
Published: January 2022

Wind turbines have a wide range of applications as the main equipment for wind-power generation because of the rapid development of technology. It is very important to select a reasonable maintenance strategy to reduce the operation and maintenance costs of wind turbines. Traditional maintenance does not consider the environmental benefits. Thus, for the maintenance problems of wind turbines, an opportunistic maintenance strategy that considers structural correlations, random correlations, and carbon emissions is proposed. First, a Weibull distribution is used to describe the deterioration trend of wind turbine subsystems. The failure rates and reliability of wind turbines are described by the random correlations among all subsystems. Meanwhile, two improvement factors are introduced into the failure rate and carbon emission model to describe imperfect maintenance, including the working-age fallback factor and the failure rate increasing factor. Then, the total expected maintenance cost can be described as the objective function for the proposed opportunistic maintenance model, including the maintenance preparation cost, maintenance adjustment cost, shutdown loss cost, and operation cost. The maintenance preparation cost is related to the economic correlation, and the maintenance adjustment cost is described by using the maintenance probabilities under different maintenance activities. The shutdown loss cost is obtained by considering the structural correlation, and the operation cost is related to the energy consumption of wind turbines. Finally, a case study is provided to analyze the performance of the proposed model. The obtained optimal opportunistic maintenance duration can be used to interpret the structural correlation coefficient, random correlation coefficient, and sensitivity of carbon emissions. Compared with preventive maintenance, the proposed model provides better performance for the maintenance problems of wind turbines and can obtain relatively good solutions in a short computation time.
Thermoeconomic Diagnosis of the Sequential Combustion Gas Turbine ABB/Alstom GT24
Authors: Castro-Hernández Sergio , López-Arenas Teresa , Torres-González Edgar Vicente , Lugo-Méndez Helen , Lugo-Leyte Raúl
Published: January 2022

In this study, we used the thermoeconomic theory to evaluate the impact of residue cost formation on the cost of electricity generated from natural gas burned in a gas turbine that applied sequential combustion; we also analyzed the impact of the combustion process on the additional fuel consumption to compensate for a malfunction component. We used the Alstom GT24 gas turbine, which applied sequential combustion and generated 235 MW of power. Thermoeconomic analysis indicated that the exergy cost of power generation was 626.33 MW (30.42% corresponded to irreversibility costs, and 29.22% and 2.84% corresponded to the formation costs of physical and chemical residues, respectively). The exergoeconomic production cost of gas turbine was 10,098.71 USD/h, 34.76% from external resources and 65.24% from capital and operating costs. Thermoeconomic diagnosis revealed that a compressor deterioration (of 1-% drop in the isentropic efficiency) resulted in an additional fuel consumption of 4.05 MW to compensate for an increase in irreversibilities (1.97 MW) and residues (2.08 MW); the compressor generated the highest cost (49.9% of additional requirement). Thus, our study can identify the origin of anomalies in a gas-turbine system and explain their effects on the rest of the components.
Decision-Making under the Risk, Uncertainty and COVID-19 Pandemic Conditions Applying the PL9A Method of Logistics Planning—Case Study
Authors: Staniuk Wiesław , Staniuk Michał , Chamier-Gliszczynski Norbert , Jacyna Marianna , Kłodawski Michał
Published: January 2022

The next industrial revolution, which coincided with the COVID-19 pandemic, is prompting a different look at the issue of supply chain change management. A new perspective should take into account the aspect of supply chain efficiency at multiple levels. Efficient logistics is green and energy-saving, both of which need to be systematically integrated with the logistical planning processes. The dynamic changes on the demand and supply side resulting from social, political, and economic transformations have significantly influenced the shaping of long-term supply chains. The development of new manufacturing and logistics technologies prompts the development and implementation of new integrated planning methods to support supply chain management processes. Modern supply chains are oriented towards operations in a dynamically changing socio-economic environment. The new methods are capable of incorporating dynamic adaptation of logistics infrastructure which respond to changing relationships between supply and demand. To meet the identified problems of complexity, relevance, and time-consumption of the logistic planning process in modern enterprise management, the PL9A method of logistic planning and 9A LOGPLANNER application for logistics planning were developed. The article presents the results of experimental and simulation studies on the improvement of logistic processes in a working manufacturing enterprise with application of the PL9A method. The results of the experimental work indicate that the application of the PL9A method embedded in the 9A LOGPLANNER software makes it possible to dynamically simulate any number of logistics system variants in a short period of time, while reducing risk and obtaining tangible benefits in terms of energy and ecological efficiency.
The Apicomplexan Parasite Toxoplasma gondii
Authors: Delgado Inês L. S. , Zúquete Sara , Santos Dulce , Basto Afonso P. , Leitão Alexandre , Nolasco Sofia
Published: January 2022

Toxoplasma gondii is a ubiquitous zoonotic parasite with an obligatory intracellular lifestyle. It relies on a specialized set of cytoskeletal and secretory organelles for host cell invasion. When infecting its felid definitive host, T. gondii undergoes sexual reproduction in the intestinal epithelium, producing oocysts that are excreted with the feces and sporulate in the environment. In other hosts and/or tissues, T. gondii multiplies by asexual reproduction. Rapidly dividing tachyzoites expand through multiple tissues, particularly nervous and muscular tissues, and eventually convert to slowly dividing bradyzoites which produce tissue cysts, structures that evade the immune system and remain infective within the host. Infection normally occurs through ingestion of sporulated oocysts or tissue cysts. While T. gondii is able to infect virtually all warm-blooded animals, most infections in humans are asymptomatic, with clinical disease occurring most often in immunocompromised hosts or fetuses carried by seronegative mothers that are infected during pregnancy.
Fuel-Specific Aggregation of Active Fire Detections for Rapid Mapping of Forest Fire Perimeters in Mexico
Authors: Briones-Herrera Carlos Ivan , Vega-Nieva Daniel José , Briseño-Reyes Jaime , Monjarás-Vega Norma Angélica , López-Serrano Pablito Marcelo , Corral-Rivas José Javier , Alvarado Ernesto , Arellano-Pérez Stéfano , Jardel Peláez Enrique J. , Pérez Salicrup Diego Rafael , Jolly William Matthew
Published: January 2022

Context and Background. Active fires have the potential to provide early estimates of fire perimeters, but there is a lack of information about the best active fire aggregation distances and how they can vary between fuel types, particularly in large areas of study under diverse climatic conditions. Objectives. The current study aimed at analyzing the effect of aggregation distances for mapping fire perimeters from active fires for contrasting fuel types and regions in Mexico. Materials and Methods. Detections of MODIS and VIIRS active fires from the period 2012–2018 were used to obtain perimeters of aggregated active fires (AGAF) at four aggregation distances (750, 1000, 1125, and 1500 m). AGAF perimeters were compared against MODIS MCD64A1 burned area for a total of 24 fuel types and regions covering all the forest area of Mexico. Results/findings. Optimum aggregation distances varied between fuel types and regions, with the longest aggregation distances observed for the most arid regions and fuel types dominated by shrubs and grasslands. Lowest aggregation distances were obtained in the regions and fuel types with the densest forest canopy and more humid climate. Purpose/Novelty. To our best knowledge, this study is the first to analyze the effect of fuel type on the optimum aggregation distance for mapping fire perimeters directly from aggregated active fires. The methodology presented here can be used operationally in Mexico and elsewhere, by accounting for fuel-specific aggregation distances, for improving rapid estimates of fire perimeters. These early fire perimeters could be potentially available in near-real time (at every satellite pass with a 12 h latency) in operational fire monitoring GIS systems to support rapid assessment of fire progression and fire suppression planning.
Why Do We Still Not Know How to Prevent Firefighter Entrapments?—Thoughts and Observations from a Few Perplexed Fire Practitioners
Authors: Gibos Kelsy , Fitzpatrick Kyle , Elliott Scott
Published: January 2022

Wildland firefighters continue to die in the line of duty. Flammable landscapes intersect with bold but good-intentioned doers and trigger entrapment—a situation where personnel is unexpectedly caught in fire behaviour-related, life-threatening positions where planned escape routes or safety zones are absent, inadequate, or compromised. We often document, share and discuss these stories, but many are missed, especially when the situation is a near miss. Entrapment continues to be a significant cause of wildland firefighter deaths. Why do we still not know how to prevent them? We review a selection of entrapment reports courtesy of the Wildland Fire Lessons Learned Centre (WFLLC) and focus on human factors involved in entrapment rather than the specifics of fire behaviour and the environment. We found that in order for operational supervisors to make more informed strategic and tactical decisions, a more holistic and complete trend analysis is necessary of the existing database of entrapment incidents. Analysis of the entrapment data would allow training to include a more fulsome understanding of when suppression resources are applying strategies and tactics that might expose them to a higher likelihood of entrapment. Operational supervisors would make more informed decisions as to where and when to deploy resources in critical situations in order to reduce the exposure to unnecessary risk of entrapment.
Numerical and Experimental Analysis of Fire Resistance for Steel Structures of Ships and Offshore Platforms
Authors: Gravit Marina , Shabunina Daria
Published: January 2022

The requirements for the fire resistance of steel structures of oil and gas facilities for transportation and production of hydrocarbons are considered (structures of tankers and offshore platforms). It is found that the requirements for the values of fire resistance of structures under hydrocarbon rather than standard fire conditions are given only for offshore stationary platforms. Experimental studies on the loss of integrity (E) and thermal insulating capacity (I) of steel bulkheads and deck with mineral wool under standard and hydrocarbon fire regimes are presented. Simulation of structure heating was performed, which showed a good correlation with the experimental results (convective heat transfer coefficients for bulkheads of class H: 50 W/m2·K; for bulkheads of class A: 25 W/m2·K). The consumption of mineral slabs and endothermic mat for the H-0 bulkhead is predicted. It is calculated that under a standard fire regime, mineral wool with a density of 80–100 kg/m2 and a thickness of 40 to 85 mm should be used; under a hydrocarbon fire regime, mineral wool with a density above 100 kg/m2 and a thickness of 60–150 mm is required. It is shown that to protect the structures of decks and bulkheads in a hydrocarbon fire regime, it is necessary to use 30–40% more thermal insulation and apply the highest density of fire-retardant material compared to the standard fire regime. Parameters of thermal conductivity and heat capacity of the applied flame retardant in the temperature range from 0 to 1000 °C were clarified.
Solving Patient Allocation Problem during an Epidemic Dengue Fever Outbreak by Mathematical Modelling
Authors: Tsai Jung-Fa , Chu Tai-Lin , Cuevas Brun Edgar Hernan , Lin Ming-Hua
Published: January 2022

Dengue fever is a mosquito-borne disease that has rapidly spread throughout the last few decades. Most preventive mechanisms to deal with the disease focus on the eradication of the vector mosquito and vaccination campaigns. However, appropriate mechanisms of response are indispensable to face the consequent events when an outbreak takes place. This study applied single and multiple objective linear programming models to optimize the allocation of patients and additional resources during an epidemic dengue fever outbreak, minimizing the summation of the distance travelled by all patients. An empirical study was set in Ciudad del Este, Paraguay. Data provided by a privately run health insurance cooperative was used to verify the applicability of the models in this study. The results can be used by analysts and decision makers to solve patient allocation problems for providing essential medical care during an epidemic dengue fever outbreak.
MiXie, an Online Tool for Better Health Assessment of Workers Exposed to Multiple Chemicals
Authors: La Rocca Bénédicte , Sarazin Philippe
Published: January 2022

There is increasing concern for workers facing multiple chemical exposure. The accumulation of information on occupational conditions indicates the need to incorporate the concept of multiple exposures in the risk assessment process and to develop tools for assessing the potential impacts of multiple exposures on workers’ health. Our objective is to describe the MiXie online decision-making tool that can be used to assess the risk of exposure to multiple chemicals. The description includes the development of MiXie, the structure of its toxicological database according to the target organ or the mode of action, and the algorithm for quantitative analysis of a mixture. Two case studies of its use in evaluating the risks of multiple exposures in real workplace situations are presented. The case study in the printing industry showed increased risk for four toxicological classes (central nervous system damage, ocular damage, skin damage, and ototoxicity) associated with co-exposure to four chemicals during maintenance operations. The MiXie analysis also showed the presence of carcinogenic substances in the mixture and a risk to the development of the foetus. The case study in nail salons showed the presence of carcinogenic and sensitizing chemicals and an increased risk to upper airways. MiXie helps preventers evaluate the possible additive effects of mixtures, providing an easy-to-read diagnosis to identify risks incurred by co-exposed employees. In addition, MiXie identifies risky occupational situations that would go unnoticed without a multiple substance approach.
Analysis of the Interaction Mechanism of the Risk Factors of Gas Explosions in Chinese Underground Coal Mines
Authors: Zhang Jinjia , Zeng Yiping , Reniers Genserik , Liu Jie
Published: January 2022

Gas explosion accidents easily cause severe casualties in Chinese underground coal mines. Systematic analysis of accident causation is crucial for the prevention of gas explosions. This study identifies the representative risk factors of gas explosions and determines the interrelationship among these risk factors to highlight weak links and develop countermeasures. A total of 21 representative risk factors of gas explosions were identified through 128 case studies and front-line investigations. On this basis, a five-level hierarchical structure model of gas explosions was established to explore the complex interrelationships among the representative risk factors based on a combination of the Decision-Making Trial and Evaluation Laboratory (DEMATEL) and Interpretive Structural Modeling (ISM) methods. Moreover, the Matrix of Cross Impact Multiplications Applied to Classification (MICMAC) method was applied to achieve risk factor classification into four clusters, namely, driving factors, linkage factors, dependent factors and autonomous factors. The results indicated that the interrelationships and emergence properties among the risk factors may cause gas explosions, which should give more attention to the interrelationships among multiple factors and multiple subsystems for coal enterprises. Meanwhile, the complex geological conditions, poor safety supervision, inadequate safety education and training, incomplete execution safety regulations and poor safety technology and input are the long-term focus of risk management for coal enterprises. Finally, 10 countermeasures were proposed to control these representative risk factors and interrelationships. The results are helpful to the development of gas explosion risk management policies and to the preferential allocation of limited resources to resolve these issues.
Compact LWFA-Based Extreme Ultraviolet Free Electron Laser: Design Constraints
Authors: Molodozhentsev Alexander Yu. , Kruchinin Konstantin O.
Published: January 2022

The combination of advanced high-power laser technology, new acceleration methods and achievements in undulator development offers the opportunity to build compact, high-brilliance free electron lasers driven by a laser wakefield accelerator. Here, we present a simulation study outlining the main requirements for the laser–plasma-based extreme ultraviolet free electron laser setup with the aim to reach saturation of the photon pulse energy in a single unit of a commercially available undulator with the deflection parameter K0 in the range of 1–1.5. A dedicated electron beam transport strategy that allows control of the electron beam slice parameters, including collective effects, required by the self-amplified spontaneous emission regime is proposed. Finally, a set of coherent photon radiation parameters achievable in the undulator section utilizing the best experimentally demonstrated electron beam parameters are analyzed. As a result, we demonstrate that the ultra-short, few-fs-level pulse of the photon radiation with the wavelength in the extreme ultraviolet range can be obtained with the peak brilliance of ∼7×1028 photons/pulse/mm2/mrad2/0.1%bw.
Cure Kinetics of Samarium-Doped Fe3O4/Epoxy Nanocomposites
Authors: Jouyandeh Maryam , Ganjali Mohammad Reza , Mehrpooya Mehdi , Abida Otman , Jabbour Karam , Rabiee Navid , Habibzadeh Sajjad , Mashahdzadeh Amin Hamed , García-Peñas Alberto , Stadler Florian J. , Saeb Mohammad Reza
Published: January 2022

To answer the question “How does lanthanide doping in iron oxide affect cure kinetics of epoxy-based nanocomposites?”, we synthesized samarium (Sm)-doped Fe3O4 nanoparticles electrochemically and characterized it using Fourier-transform infrared spectroscopy (FTIR), X-ray powder diffraction (XRD), field emission scanning electron microscopy (FE-SEM), energy dispersive X-Ray analysis (EDX), transmission electron microscopy (TEM), and X-ray photoelectron spectroscopy analyses (XPS). The magnetic particles were uniformly dispersed in epoxy resin to increase the curability of the epoxy/amine system. The effect of the lanthanide dopant on the curing reaction of epoxy with amine was explored by analyzing differential scanning calorimetry (DSC) experimental data based on a model-free methodology. It was found that Sm3+ in the structure of Fe3O4 crystal participates in cross-linking epoxy by catalyzing the reaction between epoxide rings and amine groups of curing agents. In addition, the etherification reaction of active OH groups on the surface of nanoparticles reacts with epoxy rings, which prolong the reaction time at the late stage of reaction where diffusion is the dominant mechanism.
Seasonal Accumulated Workloads in Collegiate Women’s Soccer: A Comparison of Starters and Reserves
Authors: Jagim Andrew R. , Askow Andrew T. , Carvalho Victoria , Murphy Jason , Luedke Joel A. , Erickson Jacob L.
Published: January 2022

Research quantifying the unique workload demands of starters and reserves in training and match settings throughout a season in collegiate soccer is limited. Purpose: The purpose of the current study is to compare accumulated workloads between starters and reserves in collegiate soccer. Methods: Twenty-two NCAA Division III female soccer athletes (height: 1.67 ± 0.05 m; body mass: 65.42 ± 6.33 kg; fat-free mass: 48.99 ± 3.81 kg; body fat %: 25.22 ± 4.78%) were equipped with wearable global positioning systems with on-board inertial sensors, which assessed a proprietary training load metric and distance covered for each practice and 22 matches throughout an entire season. Nine players were classified as starters (S), defined as those playing >50% of playing time throughout the entire season. The remaining 17 were reserves (R). Goalkeepers were excluded. A one-way ANOVA was used to determine the extent of differences in accumulated training load throughout the season by player status. Results: Accumulated training load and total distance covered for starters were greater than reserves ((S: 9431 ± 1471 vs. R: 6310 ± 2263 AU; p < 0.001) and (S: 401.7 ± 31.9 vs. R: 272.9 ± 51.4 km; p < 0.001), respectively) throughout the season. Conclusions: Starters covered a much greater distance throughout the season, resulting in almost double the training load compared to reserves. It is unknown if the high workloads experienced by starters or the low workloads of the reserves is more problematic. Managing player workloads in soccer may require attention to address potential imbalances that emerge between starters and reserves throughout a season.
Pore-Scale Investigation of the Electrical Property and Saturation Exponent of Archie’s Law in Hydrate-Bearing Sediments
Authors: Zhao Jinhuan , Liu Changling , Li Chengfeng , Zhang Yongchao , Bu Qingtao , Wu Nengyou , Liu Yang , Chen Qiang
Published: January 2022

Characterizing the electrical property of hydrate-bearing sediments is essential for hydrate reservoir identification and saturation evaluation. As the major contributor to electrical conductivity, pore water is a key factor in characterizing the electrical properties of hydrate-bearing sediments. The objective of this study is to clarify the effect of hydrates on pore water and the relationship between pore water characteristics and the saturation exponent of Archie’s law in hydrate-bearing sediments. A combination of X-ray computed tomography and resistivity measurement technology is used to derive the three-dimensional spatial structure and resistivity of hydrate-bearing sediments simultaneously, which is helpful to characterize pore water and investigate the saturation exponent of Archie’s law at the micro-scale. The results show that the resistivity of hydrate-bearing sediments is controlled by changes in pore water distribution and connectivity caused by hydrate formation. With the increase of hydrate saturation, pore water connectivity decreases, but the average coordination number and tortuosity increase due to much smaller and more tortuous throats of pore water divided by hydrate particles. It is also found that the saturation exponent of Archie’s law is controlled by the distribution and connectivity of pore water. As the parameters of connected pore water (e.g., porosity, water saturation) decrease, the saturation exponent decreases. At a low hydrate-saturation stage, the saturation exponent of Archie’s law changes obviously due to the complicated pore structure of hydrate-bearing sediments. A new logarithmic relationship between the saturation exponent of Archie’s law and the tortuosity of pore water is proposed which helps to calculate field hydrate saturation using resistivity logging data.
The Isolation of Vibrio crassostreae and V. cyclitrophicus in Lesser-Spotted Dogfish (Scyliorhinus canicula) Juveniles Reared in a Public Aquarium
Authors: Tomasoni Mattia , Esposito Giuseppe , Mugetti Davide , Pastorino Paolo , Stoppani Nadia , Menconi Vasco , Gagliardi Flavio , Corrias Ilaria , Pira Angela , Acutis Pier Luigi , Dondo Alessandro , Prearo Marino , Colussi Silvia
Published: January 2022

The genus Vibrio currently contains 147 recognized species widely distributed, including pathogens for aquatic organisms. Vibrio infections in elasmobranchs are poorly reported, often with identifications as Vibrio sp. and without detailed diagnostic insights. The purpose of this paper is the description of the isolation and identification process of Vibrio spp. following a mortality event of Scyliorhinus canicula juvenile reared in an Italian public aquarium. Following investigations aimed at excluding the presence of different pathogens of marine fish species (parasites, bacteria, Betanodavirus), several colonies were isolated and subjected to species identification using the available diagnostic techniques (a biochemical test, MALDI-TOF MS, and biomolecular analysis). Discrepancies were observed among the methods; the limits of biochemistry as a unique tool for Vibrio species determination were detected through statistical analysis. The use of the rpoB gene, as a diagnostic tool, allowed the identification of the isolates as V. crassostreae and V. cyclotrophicus. Although the pathogenic role of these microorganisms in lesser-spotted dogfish juveniles has not been demonstrated, and the presence of further pathogens cannot be excluded, this study allowed the isolation of two Vibrio species in less-studied aquatic organisms, highlighting the weaknesses and strengths of the different diagnostic methods applied.
Machine-Learning-Based Semiparametric Time Series Conditional Variance: Estimation and Forecasting
Authors: Dang Justin , Ullah Aman
Published: January 2022

This paper proposes a new combined semiparametric estimator of the conditional variance that takes the product of a parametric estimator and a nonparametric estimator based on machine learning. A popular kernel-based machine learning algorithm, known as the kernel-regularized least squares estimator, is used to estimate the nonparametric component. We discuss how to estimate the semiparametric estimator using real data and how to use this estimator to make forecasts for the conditional variance. Simulations are conducted to show the dominance of the proposed estimator in terms of mean squared error. An empirical application using S&P 500 daily returns is analyzed, and the semiparametric estimator effectively forecasts future volatility.
Why Does Vascular Access Dysfunction Occur despite Brachial Artery Blood Flow Being Higher than Preset Blood Flow?
Authors: Ono Jun-ichi , Oiwa Takushi , Ogasawara Yasuo , Mochizuki Seiichi
Published: January 2022

Background: In recent years, many reports have investigated the usefulness of brachial artery blood flow (BAF) measured by ultrasonography as an evaluation index for the vascular access (VA) stenosis of hemodialysis patients. However, the mechanism of VA dysfunction, despite BAF being higher than the preset blood flow, has not been clarified to date. Methods: The relationship between actual blood-removal flow and recirculation rate with decreasing VA flow was examined using a VA flow path model and pure water as a model fluid. The blood-flow rate was set at 180 mL/min, and the set VA flow rate was lowered stepwise from 350 to 50 mL/min. VA flow rate, blood-removal flow rate, and flow waveform measured between two needle-puncture sites were recorded, and then the actual blood-removal flow rate and recirculation rate were calculated. Results: Recirculation was observed at a VA flow rate < 300 mL/min. The recirculation was due to the VA flow rate, which was transiently reduced to the level below the blood-removal flow rate, resulting in backflow. In contrast, no decrease in the actual blood-removal flow rate was observed. Conclusion: It is suggested that the mechanism of the VA dysfunction, despite the BAF being higher than the preset blood-flow rate, was due to the diastolic BAF being lower than the blood-removal flow rate.
Subject–Verb Number Agreement in Bilingual Processing: (Lack of) Age of Acquisition and Proficiency Effects
Authors: Sagarra Nuria , Rodriguez Nicole
Published: January 2022

Children acquire language more easily than adults, though it is controversial whether this faculty declines as a result of a critical period or something else. To address this question, we investigate the role of age of acquisition and proficiency on morphosyntactic processing in adult monolinguals and bilinguals. Spanish monolinguals and intermediate and advanced early and late bilinguals of Spanish read sentences with adjacent subject–verb number agreements and violations and chose one of four pictures. Eye-tracking data revealed that all groups were sensitive to the violations and attended more to more salient plural and preterit verbs than less obvious singular and present verbs, regardless of AoA and proficiency level. We conclude that the processing of adjacent SV agreement depends on perceptual salience and language use, rather than AoA or proficiency. These findings support usage-based theories of language acquisition.
A Comparative and Comprehensive Review of Antibody Applications in the Treatment of Lung Disease
Authors: Wu Yuefeng , Song Hai
Published: January 2022

Antibodies are a type of protein produced by active B cells in response to antigen stimulation. A series of monoclonal antibodies and neutralizing antibodies have been invented and put into clinical use because of their high therapeutic effect and bright developing insight. Patients with cancer, infectious diseases, and autoimmune diseases can all benefit from antibody therapy. However, the targeting aspects and potential mechanisms for treating these diseases differ. In the treatment of patients with infectious diseases such as COVID-19, neutralizing antibodies have been proposed as reliable vaccines against COVID-19, which target the ACE2 protein by preventing virus entry into somatic cells. Monoclonal antibodies can target immune checkpoints (e.g., PD-L1 and CTLA-4), tyrosine kinase and subsequent signaling pathways (e.g., VEGF), and cytokines in cancer patients (e.g. IL-6 and IL-1β). It is debatable whether there is any connection between the use of antibodies in these diseases. It would be fantastic to discover the related points and explain the burden for the limitation of cross-use of these techniques. In this review, we provided a comprehensive overview of the use of antibodies in the treatment of infectious disease and cancer patients. There are also discussions of their mechanisms and history. In addition, we discussed our future outlook on the use of antibodies.
Using Integrated MMD-TOPSIS to Solve the Supplier Selection and Fair Order Allocation Problem: A Tunisian Case Study
Authors: Aouadni Sourour , Euchi Jalel
Published: January 2022

Currently, the supplier selection process is considered as an integral part of the supply chain. The appropriate selection of suppliers plays a preponderant role in the performance chain of supply as it determines relevant aspects such as cost management and flexibility of most production processes. Background: It is considered a multi-criteria and multi-objective problem because it includes both qualitative and quantitative factors. Method: To solve the Supplier Selection and Fair Order Allocation Problem (SSFOAP), a hybrid solution methodology based on the best–worst method (BWM) and MMD-TOPSIS techniques in the first phase has been developed to find a robust ranking of suppliers. In the second phase to determine the weight of the objective function, the Linear Programming (LP) approach is used. Results: This proposed model can help decisionmakers find the right orders for each supplier and enable purchasing managers to manage supply chain performance in terms of cost, quality, and service. To test the performance of our solution methodology, we apply our hybrid technique to solve a real case of the Tunisian Electric Society (TSE). Cplex software is used to solve bi-objective programming and to answer strategic questions. Conclusions: The experimental results indicate that the combination of MMD-TOPSIS and bi-objective programming provide effective gain concerning solution quality compared with the given solution of the administrator of TSE.
The Effect of Inflow Distortion on the Rotordynamic Characteristics of a 1400-MW Reactor Coolant Pump Annular Seal
Authors: Zhou Lusheng , Wang Xiaofang , Liu Haitao , Xin Jianchi
Published: January 2022

The annular seal between stator and rotor substantively acts as a bearing that affects the rotordynamic characteristic of the turbomachinery rotor system. The rotor wake turbulence in a canned motor Reactor Coolant Pump (RCP) will lead to inflow pressure distortion at the annular seal entrance, thus further affecting the seal rotordynamic characteristics and threatening the stable operation of RCP. In order to obtain the seal rotordynamic coefficients, a transient numerical method applies the mesh deformation technique to simulate the multiple-frequency elliptical rotor whirling orbit model. The transient solutions were proposed to solve the unsteady reaction forces of annular seals at five excitation frequencies for each case. The inflow pressure distortion patterns were simplified as harmonic functions, including two important influence parameters that are impeller blades number m and pressure fluctuation ratio λ. The numerical results showed that with nonuniform time-averaged pressure distribution at the entrance of the annular seal in Case 2, the inflow distortion significantly affects the seal rotordynamic coefficients, while the rotational spinning speed in Case 3 can weaken the time-averaged nonuniformity and accordingly make a dent in the influence. Increasing impeller blades number m and pressure fluctuation λ both result in a sharp diminution of the negative stiffness Keff, as well as an obvious increase in the effective damping Ceff, which will strengthen rotor misalignment and system stability. In addition, the larger impeller blades number m and higher pressure fluctuation λ will make the effective damping Ceff more independent of the whirling frequency. These results provide theoretical guidance for the operation safety of RCP.
A Transfer Learning Evaluation of Deep Neural Networks for Image Classification
Authors: Abou Baker Nermeen , Zengeler Nico , Handmann Uwe
Published: January 2022

Transfer learning is a machine learning technique that uses previously acquired knowledge from a source domain to enhance learning in a target domain by reusing learned weights. This technique is ubiquitous because of its great advantages in achieving high performance while saving training time, memory, and effort in network design. In this paper, we investigate how to select the best pre-trained model that meets the target domain requirements for image classification tasks. In our study, we refined the output layers and general network parameters to apply the knowledge of eleven image processing models, pre-trained on ImageNet, to five different target domain datasets. We measured the accuracy, accuracy density, training time, and model size to evaluate the pre-trained models both in training sessions in one episode and with ten episodes.
NER in Archival Finding Aids: Extended
Authors: Cunha Luís Filipe da Costa , Ramalho José Carlos
Published: January 2022

The amount of information preserved in Portuguese archives has increased over the years. These documents represent a national heritage of high importance, as they portray the country’s history. Currently, most Portuguese archives have made their finding aids available to the public in digital format, however, these data do not have any annotation, so it is not always easy to analyze their content. In this work, Named Entity Recognition solutions were created that allow the identification and classification of several named entities from the archival finding aids. These named entities translate into crucial information about their context and, with high confidence results, they can be used for several purposes, for example, the creation of smart browsing tools by using entity linking and record linking techniques. In order to achieve high result scores, we annotated several corpora to train our own Machine Learning algorithms in this context domain. We also used different architectures, such as CNNs, LSTMs, and Maximum Entropy models. Finally, all the created datasets and ML models were made available to the public with a developed web platform, NER@DI.
Prediction of Airfoil Stall Based on a Modified k−v2¯−ω Turbulence Model
Authors: Wu Chenyu , Li Haoran , Zhang Yufei , Chen Haixin
Published: January 2022

The accuracy of an airfoil stall prediction heavily depends on the computation of the separated shear layer. Capturing the strong non-equilibrium turbulence in the shear layer is crucial for the accuracy of a stall prediction. In this paper, different Reynolds-averaged Navier–Stokes turbulence models are adopted and compared for airfoil stall prediction. The results show that the separated shear layer fixed k−v2¯−ω (abbreviated as SPF k−v2¯−ω) turbulence model captures the non-equilibrium turbulence in the separated shear layer well and gives satisfactory predictions of both thin-airfoil stall and trailing-edge stall. At small Reynolds numbers (Re~105), the relative error between the predicted CL,max of NACA64A010 by the SPF k−v2¯−ω model and the experimental data is less than 3.5%. At high Reynolds numbers (Re~106), the CL,max of NACA64A010 and NACA64A006 predicted by the SPF k−v2¯−ω model also has an error of less than 5.5% relative to the experimental data. The stall of the NACA0012 airfoil, which features trailing-edge stall, is also computed by the SPF k−v2¯−ω model. The SPF k−v2¯−ω model is also applied to a NACA0012 airfoil, which features trailing-edge stall and an error of CL relative to the experiment at CL>1.0 is smaller than 3.5%. The SPF k−v2¯−ω model shows higher accuracy than other turbulence models.