bluuebunny/crossref_metadata_2025 huggingface dataset:
Challenges with Assessing and Treating Pain in Research Primates: A Focused Survey and Literature Review
Authors: Paterson Emilie A. , Turner Patricia V.
Published: September 2022

Research primates may undergo surgical procedures making effective pain management essential to ensure good animal welfare and unbiased scientific data. Adequate pain mitigation is dependent on whether veterinarians, technicians, researchers, and caregivers can recognize and assess pain, as well as the availability of efficacious therapeutics. A survey was conducted to evaluate primate veterinary approaches to pain assessment and alleviation, as well as expressed challenges for adequately managing primate pain. The survey (n = 93 respondents) collected information regarding institutional policies and procedures for pain recognition, methods used for pain relief, and perceived levels of confidence in primate pain assessment. Results indicated that 71% (n = 60) of respondents worked at institutions that were without formal experimental pain assessment policies. Pain assessment methods were consistent across respondents with the majority evaluating pain based on changes in general activity levels (100%, n = 86) and food consumption (97%, n = 84). Self-reported confidence in recognizing and managing pain ranged from slightly confident to highly confident, and there was a commonly expressed concern about the lack of objective pain assessment tools and science-based evidence regarding therapeutic recommendations of analgesics for research primates. These opinions correspond with significant gaps in the primate pain management literature, including limited specific pharmacokinetic data and efficacy testing for commonly used analgesics in research primate species as well as limited research on objective and specific measures of pain in research primates. These results demonstrate that there are inconsistencies in institutional policies and procedures surrounding pain management in research primates and a lack of objective pain assessment methods. Demonstrating the gaps and challenges in primate pain management can inform guideline development and suggest areas for future research.
Influence of Increased Freedom of Movement on Welfare and Egg Laying Pattern of Hens Kept in Aviaries
Authors: Nannoni Eleonora , Buonaiuto Giovanni , Martelli Giovanna , Lizzi Gabriele , Trevisani Giacomo , Garavini Gloria , Sardi Luca
Published: September 2022

This work investigates the effects of structural modifications on the welfare level and laying patterns of hens in a three-tier commercial aviary system. Four experimental groups were used: C (control, housed in a traditional aviary); LM (longitudinal movement, in which internal partitions were removed); VM (vertical movement, in which ramps were installed); and FM (freedom of movement, both LM and VM modifications). Hens showed worse body condition scores (p < 0.05) in all the modified aviaries, while plumage condition was improved in FM but worsened in VM (p < 0.05). No significant effect was observed on egg deposition patterns, egg quality or keel bone damage. When ramps were available (VM and FM groups), hens reduced the number of flights and increased the number of walks from 0.52 to 7.7% of the displacements on average (p < 0.05). Apart from some feather pecking concerns in VM (likely due to overcrowding in some favourite aviary areas), LM and FM seemed to facilitate animal movement and promote species–specific behaviour. It is concluded that hen welfare in aviary systems can be improved by means of tailored structural modifications. Producers may therefore adopt some of these modifications (providing ramps and/or removing vertical barriers) to enhance the welfare of hens.
The Anti-Fungal Activity of Nitropropenyl Benzodioxole (NPBD), a Redox-Thiol Oxidant and Tyrosine Phosphatase Inhibitor
Authors: Nicoletti Gina , White Kylie
Published: September 2022

Phylogenetically diverse fungal species are an increasing cause of severe disease and mortality. Identification of new targets and development of new fungicidal drugs are required to augment the effectiveness of current chemotherapy and counter increasing resistance in pathogens. Nitroalkenyl benzene derivatives are thiol oxidants and inhibitors of cysteine-based molecules, which show broad biological activity against microorganisms. Nitropropenyl benzodioxole (NPBD), one of the most active antimicrobial derivatives, shows high activity in MIC assays for phylogenetically diverse saprophytic, commensal and parasitic fungi. NPBD was fungicidal to all species except the dermatophytic fungi, with an activity profile comparable to that of Amphotericin B and Miconazole. NPBD showed differing patterns of dynamic kill rates under different growth conditions for Candida albicans and Aspergillus fumigatus and was rapidly fungicidal for non-replicating vegetative forms and microconidia. It did not induce resistant or drug tolerant strains in major pathogens on long term exposure. A literature review highlights the complexity and interactivity of fungal tyrosine phosphate and redox signaling pathways, their differing metabolic effects in fungal species and identifies some targets for inhibition. A comparison of the metabolic activities of Amphotericin B, Miconazole and NPBD highlights the multiple cellular functions of these agents and the complementarity of many mechanisms. The activity profile of NPBD illustrates the functional diversity of fungal tyrosine phosphatases and thiol-based redox active molecules and contributes to the validation of tyrosine phosphatases and redox thiol molecules as related and complementary selective targets for antimicrobial drug development. NPBD is a selective antifungal agent with low oral toxicity which would be suitable for local treatment of skin and mucosal infections.
Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and Bordetella bronchiseptica Co-Infection in a Stem Cell Transplant Patient
Authors: Pierce Michael , Slipke Wendy , Biagi Mark
Published: September 2022

Bordetella bronchiseptica infections may be overlooked by clinicians due to the uncommon encounter of this pathogen in humans and common isolation of co-pathogens. However, the isolation of B. bronchiseptica in immunocompromised individuals may represent a true infection. We report our experience with the fatal case of a stem cell transplant recipient, co-infected with SARS-CoV-2 and B. bronchiseptica, who was considered fully vaccinated (two doses) at the time of her case in spring 2021. Future studies are needed to evaluate the incidence of bacterial co-infections in immunosuppressed individuals with SARS-CoV-2 and clinicians should remain cognizant of the potential pathogenic role of uncommon pathogens isolated in these individuals.
NADPH Oxidase Mediates Oxidative Stress and Ventricular Remodeling through SIRT3/FOXO3a Pathway in Diabetic Mice
Authors: Qiu Jiuchun , Liu Daiqi , Li Pengsha , Zhou Lingling , Zhou Lu , Liu Xing , Zhang Yue , Yuan Meng , Tse Gary , Li Guangping , Liu Tong
Published: September 2022

Oxidative stress and mitochondrial dysfunction are important mechanisms of ventricular remodeling, predisposed to the development of diabetic cardiomyopathy (DCM) in type 2 diabetes mellitus. In this study, we have successfully established a model of type 2 diabetes using a high-fat diet (HFD) in combination with streptozotocin (STZ). The mice were divided into three groups of six at random: control, diabetes, and diabetes with apocynin and the H9c2 cell line was used as an in vitro model for investigation. We examined the molecular mechanisms of nicotinamide adenine dinucleotide phosphate (NADPH) oxidase activation on mitochondrial dysfunction and ventricular remodeling in the diabetic mouse model. Hyperglycemia-induced oxidative stress led to a reduced expression of sirtuin 3 (SIRT3), thereby promoting forkhead box class O 3a (FOXO3a) acetylation in ventricular tissue and H9c2 cells. Reactive oxygen species (ROS) overproduction promoted ventricular structural modeling and conduction defects. These alterations were mitigated by inhibiting NADPH oxidase with the pharmaceutical drug apocynin (APO). Apocynin improved SIRT3 and Mn-SOD expression in H9c2 cells transfected with SIRT3 siRNA. In our diabetic mouse model, apocynin improved myocardial mitochondrial function and ROS overproduction through the recovery of the SIRT3/FOXO3a pathway, thereby reducing ventricular remodeling and the incidence of DCM.
Pharmacotherapies and Aortic Heme Oxygenase-1 Expression in Patients with Abdominal Aortic Aneurysm
Authors: Hofmann Anja , Hamann Bianca , Klimova Anna , Müglich Margarete , Wolk Steffen , Busch Albert , Frank Frieda , Sabarstinski Pamela , Kapalla Marvin , Nees Josef Albin , Brunssen Coy , Poitz David M. , Morawietz Henning , Reeps Christian
Published: September 2022

Background: Treatment of cardiovascular risk factors slows the progression of small abdominal aortic aneurysms (AAA). Heme oxygenase-1 (HO-1) is a stress- and hemin-induced enzyme providing cytoprotection against oxidative stress when overexpressed. However, nothing is known about the effects of cardiometabolic standard therapies on HO-1 expression in aortic walls in patients with end-stage AAA. Methods: The effects of statins, angiotensin-converting enzyme (ACE) inhibitors, angiotensin II receptor blockers (ARBs), calcium channel blockers (CCBs), beta-blockers, diuretics, acetylsalicylic acid (ASA), and therapeutic anticoagulation on HO-1 mRNA and protein expressions were analyzed in AAA patients using multivariate logistic regression analysis and comparison of monotherapy. Results: Analysis of monotherapy revealed that HO-1 mRNA and protein expressions were higher in patients on diuretics and lower in patients on statin therapy. Tests on combinations of antihypertensive medications demonstrated that ACE inhibitors and diuretics, ARBs and diuretics, and beta-blockers and diuretics were associated with increase in HO-1 mRNA expression. ASA and therapeutic anticoagulation were not linked to HO-1 expression. Conclusion: Diuretics showed the strongest association with HO-1 expression, persisting even in combination with other antihypertensive medications. Hence, changes in aortic HO-1 expression in response to different medical therapies and their effects on vessel wall degeneration should be analyzed in future studies.
Evaluation of Hepatic Detoxification Effects of Enteromorpha prolifera Polysaccharides against Aflatoxin B1 in Broiler Chickens
Authors: Liu Wen-Chao , Yang Yu-Ying , Pushparaj Karthika , Balasubramanian Balamuralikrishnan
Published: September 2022

Aflatoxin B1 (AFB1) is a major risk factor in animal feed. Seaweed (Enteromorpha prolifera)-derived polysaccharides (SDP) are natural antioxidants with multiple biological functions, which may have an in vivo detoxification effect on AFB1. The current study aimed to evaluate whether SDP could mitigate AFB1-induced hepatotoxicity in broilers. A total of 216 chickens (male, 5 weeks old) were randomly allocated to three groups with differing feeding patterns, lasting 4 weeks: (1) control group (CON, fed a basal diet); (2) AFB1 group (fed a basal diet mixed with 0.1 mg/kg AFB1); and (3) AFB1 + SDP group (AFB1 group + 0.25% SDP). The results showed that dietary SDP improved the liver function-related biochemical indicators in serum, and reversed the increase in relative liver weight, hepatic apoptosis and histological damage of broilers exposed to AFB1. SDP treatment also reduced the activity and mRNA expression of phase I detoxification enzymes, while increasing the activity and mRNA expression of phase II detoxification enzymes in the livers of AFB1-exposed broilers, which was involved in the activation of p38 mitogen-activated protein kinase (p38MAPK)/nuclear factor erythroid 2-related factor 2 (Nrf2) signaling. In conclusion, dietary SDP alleviated AFB1-induced liver injury of broilers through inhibiting phase I detoxification enzymes and upregulating p38MAPK/Nrf2-mediated phase II detoxification enzymes pathway.
Mathematical Modeling and Robust Control of a Restricted State Suspended Biped Robot Implementing Linear Actuators for Articulation Mobilization
Authors: Rincon-Martinez Karla , Chairez Isaac , Liu Wen-Yu
Published: September 2022

The aim of this study is to develop an adaptive automatic control method for solving the trajectory tracking problem for a biped robotic device (BRD) and taking into account that each articulation is mobilized by a linear actuator. Each extremity of the BRD has three articulations with a linear actuator enforcing the controlled motion for each articulation. The control problem considers the task of tracking reference trajectories that define a regular gait cycle. The suggested adaptive control form has state-dependent gains that drive the tracking error into an invariant and attractive ellipsoidal with a center at the origin; meanwhile, the articulation restrictions are satisfied permanently. The stability analysis based on a controlled Lyapunov function depending on the tracking error leads to the explicit design of the state-dependent adaptive gains. Taking into account the forward complete setting of the proposed BRD, an output feedback formulation of the given adaptive controller is also developed using a finite-time and robust convergent differentiator based on the super-twisting algorithm. A virtual dynamic representation of the BRD is used to test the proposed controller using a distributed implementation of the adaptive controller. Numerical simulations corroborate the convergence of the tracking error, while all the articulation restrictions are satisfied using the adaptive gains. With the purpose of characterizing the proposed controller, a sub-optimal tuned regular state feedback controller is used as a comparative approach for validating the suggested design. Among the compared controllers, the analysis of the convergence of the mean square error of the tracking error motivates the application of the designed adaptive variant.
Semi-Supervised Transfer Learning Methodology for Fault Detection and Diagnosis in Air-Handling Units
Authors: Martinez-Viol Victor , Urbano Eva M. , Torres Rangel Jose E. , Delgado-Prieto Miguel , Romeral Luis
Published: September 2022

Heating, ventilation and air-conditioning (HVAC) systems are the major energy consumers among buildings’ equipment. Reliable fault detection and diagnosis schemes can effectively reduce their energy consumption and maintenance costs. In this respect, data-driven approaches have shown impressive results, but their accuracy depends on the availability of representative data to train the models, which is not common in real applications. For this reason, transfer learning is attracting growing attention since it tackles the problem by leveraging the knowledge between datasets, increasing the representativeness of fault scenarios. However, to date, research on transfer learning for heating, ventilation and air-conditioning has mostly been focused on learning algorithmic, overlooking the importance of a proper domain similarity analysis over the available data. Thus, this study proposes the design of a transfer learning approach based on a specific data selection methodology to tackle dissimilarity issues. The procedure is supported by neural network models and the analysis of eventual prediction uncertainties resulting from the assessment of the target application samples. To verify the proposed methodology, it is applied to a semi-supervised transfer learning case study composed of two publicly available air-handling unit datasets containing some fault scenarios. Results emphasize the potential of the proposed domain dissimilarity analysis reaching a classification accuracy of 92% under a transfer learning framework, an increase of 37% in comparison to classical approaches.
Polysaccharides from Moroccan Green and Brown Seaweed and Their Derivatives Stimulate Natural Defenses in Olive Tree Leaves
Authors: Aitouguinane Meriem , Alaoui-Talibi Zainab El , Rchid Halima , Fendri Imen , Abdelkafi Slim , El-Hadj Mohamed Didi Ould , Boual Zakaria , Dubessay Pascal , Michaud Philippe , Traïkia Mounir , Pierre Guillaume , El Modafar Cherkaoui , Delattre Cédric
Published: September 2022

This study aims to assess for the first time the ability of marine polysaccharides and their derivatives to stimulate natural defenses in olive tree leaves. Alginates, ALSM, and ALCM were isolated from the brown algae Sargassum muticum and Cystoseira myriophylloides, respectively. The OASM and OACM fractions were obtained after radical depolymerization of ALSM and ALCM, respectively. Three sulfated polysaccharides, arabinogalactans (AGB and AGP) and fucoidans (FUCCM) were extracted from the green alga Codium decorticatum and the brown seaweed C. myriophylloides, respectively. The extraction yield of different extracts was in the range of 0.82–32% and the average molecular weight (Mw) varied from 3000 Da to 2173 kDa. The M/G ratios of ALSM and ALCM were 0.87 and 1.12, respectively. FUCCM contained 53% of fucose and 12.83% of sulfates. The AGB and AGP fractions were characterized by the presence of a high degree of sulfation and protein (12–23% (w/w)) and were composed mainly of galactose, glucose, and arabinose. The aqueous saccharide solutions were applied to the leaf discs of the olive tree at 0.5 g/L, 1 g/L, and 2 g/L, for 24 h. These molecules triggered defense responses, by showing a differential capacity to induce the activity of the phenylalanine and tyrosine ammonia-lyase (TAL and PAL), polyphenols, and lignin contents in the leaves of the olive tree. Alginates and their derivatives as well as arabinogalactans exhibited an important induction of TAL activity compared to the PAL. The sulfated polysaccharides were more effective compared to the unsulfated polysaccharides (alginates) which were active at a low concentration. The optimum concentration for most of the studied elicitors was 2 g/L. These results suggest the valorization of these molecules derived from marine biomass as inducers of natural defenses of the olive tree to protect against phytopathogens in the context of sustainable development.
A Classification Feature Optimization Method for Remote Sensing Imagery Based on Fisher Score and mRMR
Authors: Lv Chengzhe , Lu Yuefeng , Lu Miao , Feng Xinyi , Fan Huadan , Xu Changqing , Xu Lei
Published: September 2022

In object-oriented remote sensing image classification experiments, the dimension of the feature space is often high, leading to the “dimension disaster”. If a reasonable feature selection method is adopted, the classification efficiency and accuracy of the classifier can be improved. In this study, we took GF-2 remote sensing imagery as the research object and proposed a feature dimension reduction algorithm combining the Fisher Score and the minimum redundancy maximum relevance (mRMR) feature selection method. First, the Fisher Score was used to construct a feature index importance ranking, following which the mRMR algorithm was used to select the features with the maximum correlation and minimum redundancy between categories. The feature set was optimized using this method, and remote sensing images were automatically classified based on the optimized feature subset. Experimental analysis demonstrates that, compared with the traditional mRMR, Fisher Score, and ReliefF methods, the proposed Fisher Score–mRMR (Fm) method provides higher accuracy in remote sensing image classification. In terms of classification accuracy, the accuracy of the Fm feature selection method with RT and KNN classifiers is improved compared with that of single feature selection method, reaching 95.18% and 96.14%, respectively, and the kappa coefficient reaches 0.939 and 0.951, respectively.
Institutional Adoption and Implementation of Blended Learning in the Era of Intelligent Education
Authors: Zhang Chunhui , Wen Mingang , Tong Kuang , Chen Zexuan , Wen Qing , Yang Tingting , Liu Qijun
Published: September 2022

Blended learning (BL) reform is one of the vital methods to improve the teaching quality of institutions in the intelligent education era. However, institutions are always faced with many obstacles (instructors’ reluctance/inability to change, etc.) in conducting the reform. What is worse, very few studies have reported the design and effect of such a transformation. This study designed an intervention of institutional BL reform by making a unified deployment based on Graham et al.’s BL adoption framework: identifying strategy, structure, and support issues at three developmental stages. More than 900 courses (involving more than 14,000 students and more than 2000 instructors) within S university were taken as a sample. A quasi-experiment was designed to investigate the effect of the intervention on S university’s BL course transformation, students’ learning, instructors’ professional development, etc. Course logs, responses to students’ course evaluation forms, and instructors’ questionnaires were collected and analyzed. Results indicated that S university systematically conducted the BL transformation and gradually reached the mature implementation stage within 7 years. This study contributes to the literature by reporting a best practice of BL institutional adoption. Three implications, relating to strategy, structure, and support, were drawn to shed light for other institutions in moving forward on BL adoption.
Effect of Lactic Acid Bacteria on Nutritional and Sensory Quality of Goat Organic Acid-Rennet Cheeses
Authors: Kajak-Siemaszko Katarzyna , Zielińska Dorota , Łepecka Anna , Jaworska Danuta , Okoń Anna , Neffe-Skocińska Katarzyna , Trząskowska Monika , Sionek Barbara , Szymański Piotr , Dolatowski Zbigniew J. , Kołożyn-Krajewska Danuta
Published: September 2022

The aim of this study was to evaluate the applicability of selected Lactobacillus strains, previously isolated from spontaneously fermented foods, as starter cultures in the production of organic dairy products—acid-rennet goat’s cheeses under industrial conditions. The basic composition and the effect of starter cultures on the physicochemical, microbiological, sensory as well textural properties during the production and storage of goat’s cheese were evaluated. Lactic acid bacteria count in cheese samples was at a high level of about 8 log CFU/g. The cheeses made with Levilactobacillus brevis B1 and Lactiplantibacillus plantarum Os2 bacterial cultures additions have showed more favorable Lipid Quality Indices than for the control one with the addition of acid whey. The time of ripening of the cheeses significantly (p < 0.005) changed their consistency—they became softer and more elastic and less moist. It is possible that the selected cultures of L. brevis B1 and L. plantarum Os2 isolated from traditional cheeses can be successfully applied to goat’s milk cheese production. The strain L. brevis B1 is highly recommended as a starter culture for goat’s milk cheese production, taking into account the good microbiological and sensory quality as well as the chemical composition.
Research on Optimization Design of Key Energy-Absorbing Structure of a Helicopter Seat Based on Human–Seat Coupling System
Authors: Wang Xingye , Li Yanjun , Cao Yuyuan , Li Xudong , Duan Shixuan , Zhao Zejian
Published: September 2022

During the process of emergency landing, the energy of the impact in the vertical direction is dissipated through the deformation of the structure. The landing load is transferred to the spine of the occupant through the landing gear, the fuselage and finally the seat. This can cause serious damage to the human body. Since the seat is in direct contact with the human body, the energy absorption capacity of the seat is the most direct manifestation of the Crashworthiness of the helicopter. The solutions proposed in the paper may reduce the impact of the seat on the spine of the occupant during the collision by optimizing the key energy-absorbing structure. Taking the seat of the H135 helicopter as a case, the mechanical model of the human–seat coupling system, which is based on the theories of energy methods and structural mechanics, is simplified. Additionally, the simulation was considered reasonable by comparing the simulation results with the results of crashworthiness tests. On the basis of the above, the optimization of the key energy-absorbing structure of the seat was completed by using Latin hypercube sampling and the kriging model. Overall, the optimization effectively enhanced the crashworthiness of this helicopter seat and provided a solution for the passive safety design of aviation seats.
Low Compressibility at the Transition Zone of Railway Tracks Reinforced with Cement-Treated Gravel and a Geogrid under Construction
Authors: Park Seongyong , Kim Dae Sang , Kim Ungjin , Jeong Sangseom
Published: September 2022

In the transition zone of railway tracks, track irregularities occur frequently due to differential settlement, which arises from the difference between the vertical supporting stiffness of the abutment and the backfill. This is disadvantageous because it increases the maintenance requirements and deteriorates the ride quality. To address this challenge, this study proposes a strategy involving the application of cement-treated gravel reinforced with geogrids and rigid facing walls. The reinforced subgrade for railways (RSR), which can reduce residual settlement through the initial construction of the backfill reinforced with geogrids and the subsequent development of the rigid facing wall, was constructed at the transition zone with cement-treated gravel as the backfill material. The long-term behaviors during and after construction on the RSR for a period of 16 months were evaluated by analyzing the surface and ground settlements, horizontal earth pressure, and geogrid strain. The minor net settlement of the reinforced backfill converges at the early stage of subgrade construction, and the horizontal earth pressure was approximately reduced to the level of 54–63% of the Rankine active earth pressure.
A Fault Diagnosis Model for Tennessee Eastman Processes Based on Feature Selection and Probabilistic Neural Network
Authors: Xu Haoxiang , Ren Tongyao , Mo Zhuangda , Yang Xiaohui
Published: September 2022

Since the classification methods mentioned in previous studies are currently unable to meet the accuracy requirements for fault diagnosis in large-scale chemical industries, these methods are gradually being eliminated and rarely used. This research offers a probabilistic neural network (PNN) based on feature selection and a bio-heuristic optimizer as a fault diagnostic approach for chemical industries using artificial intelligence. The sample characteristics are initially simplified using heuristic feature selection and support vector machine recursive feature elimination (SVM-RFE). Using PNN as the principal classifier of the fault diagnostic model and employing a modified salp swarm algorithm (MSSA) linked with the bio-heuristic optimizer to optimize the hidden smoothing factor (σ) of PNN further improves the classification performance of PNN. The MSSA introduces the Lévy flight method, greatly enhancing exploration capabilities and convergence speed compared to the standard SSA. To validate the engineering application of the suggested method, a PSO-SVM-REF-MSSA-PNN model is created, and TE process data are utilized in tests. The model’s performance is evaluated by comparing its accuracy and F1-score to other regularly used classification models. The results indicate that the data samples selected by PSO-SVM-RFE features simplify and eliminate redundant features more effectively than other feature selection techniques. The MSSA algorithm’s optimization capabilities surpass those of conventional optimization techniques. The PNN network is more suitable for fault detection and classification in the chemical industry. The three considerations listed above make it evident that the proposed approach might greatly help identify TE process problems.
Shannon Entropy Analysis of Reservoir-Triggered Seismicity at Song Tranh 2 Hydropower Plant, Vietnam
Authors: Telesca Luciano , Thai Anh Tuan , Lovallo Michele , Cao Dinh Trong , Nguyen Le Minh
Published: September 2022

The reservoir-triggered seismicity at the Song Tranh 2 reservoir in Vietnam is investigated by using Shannon entropy, a well-known informational method used to analyze complexity in time series in terms of disorder and uncertainty. The application of the time-varying Shannon entropy to the time series of the interevent times of seismicity has evidenced clear links with the temporal fluctuations of the water level of the reservoir, strengthening the belief that the reservoir operational regime is one of the sources of the seismicity occurring in the area. Shannon entropy has also shed light on the tectonic mechanisms of generation of reservoir-triggered seismicity, revealing that the change in stress due to the variation in water level causes the seismic system to be in a state of greater disorder and instability, well depicted by Shannon entropy, which would lead to an increase in seismic activity.
Electrothermally Activated CNT/GNP-Doped Anti-icing and De-Icing Systems: A Comparison Study of 3D Printed Circuits versus Coatings
Authors: Cortés Alejandro , Jiménez-Suárez Alberto , Ureña Alejandro , Prolongo Silvia G. , Campo Mónica
Published: September 2022

The present work studies the electrical and electrothermal properties of CNT/GNP-doped nanocomposites for optimizing their anti-icing and de-icing capabilities. Here, a comparison between 3D-printed circuits and coatings based on these materials is carried out. In this regard, the higher electrical conductivity that is achieved by the specimens when increasing the nanoparticle content and the higher cross-sectional area of the coatings with regard to the 3D-printed circuits induces a higher heat generated by the Joule’s effect. Moreover, the successful de-icing test performed by the specimen with the highest self-heating capability, evinces that the studied nanocomposites are suitable for de-icing purposes.
Special Issue on Machine Learning and Natural Language Processing
Authors: Mozgovoy Maxim , Suero Montero Calkin
Published: September 2022

The task of processing natural language automatically has been on the radar of researchers since the dawn of computing, fostering the rise of fields such as computational linguistics and human–language technologies [...]
Simulation Study of the Capture and Purification Performance of Exhaust Fume Systems in Chinese Commercial Kitchens—Case Study in Tianjin
Authors: Zhang Awen , Deng Na , Long Zhengwei , Hao Ruisen , Shen Changyu , Cao Guoqing
Published: September 2022

A Chinese commercial kitchen fume exhaust (CCKEF) system mainly consists of a wall-mounted canopy hood, air duct and terminal electrostatic purifiers, the capture and purification performance of which should be guaranteed to obtain satisfactory indoor and outdoor air environment in engineering applications. However, few studies have focused on the operation performance of CCKEF systems. This study was aimed at providing a simulation method to investigate the operation performance of such systems. The simulation model of a representative CCKEF system was established using CFD software and validated with measured temperature, air velocity and purification efficiency with a deviation within 10%. The validated model was used to predict the indoor air environment and purification efficiency of the CCKEF system under different working conditions. The results showed that the temperature of transfer air from adjacent rooms had a greater impact on the thermal environment of the cooking area than the surface temperature of stoves. The exhaust air volume had a significant influence on both the indoor air environment and purification efficiency. CCKEF system was suggested to be operated at the optimum airflow according to the simultaneous coefficient of stoves as the energy consumption of the system can be saved by 3.75%.
Acoustic Propagation Characteristics of Unsaturated Porous Media Containing CO2 and Oil
Authors: Qi Yujuan , Zhang Xiumei , Liu Lin
Published: September 2022

Carbon dioxide geological utilization and storage (CGUS) is an effective way to mitigate climate warming. In this paper, we resorted to Lo’s model to analyze the dispersion and attenuation characteristics of unsaturated porous media. Based on this, we analyzed the sensitivity of the first compressional wave (P1) and the shear wave (S) to various physical parameters. In addition, the modified models of live oil’s velocity and density were proposed, which were verified by experimental data under the consideration of CO2 dissolution. It is shown that the velocities and attenuations of P1 and S waves are influenced by various parameters, especially CO2 saturation and pore fluid parameters, such as density and velocity. In particular, with increasing CO2 saturation, the sensitivity of P1 velocity decreases, while that of the S velocity increases. Better monitoring results can be achieved by combining P1 and S waves. Finally, the acoustic response was analyzed under the modified model. With the increase in CO2 saturation, the P1 velocity decreases, while the S velocity becomes almost constant and then linearly increases, with the trend changing at the critical saturation. The study provides a more precise basis for monitoring the security of CO2 injection in CGUS.
A Compact Broadband Planar Inverted-F Antenna with Dual-Resonant Modes
Authors: Qi Zhengya , Ding Xinhao , Yang Wenwen , Chen Jianxin
Published: September 2022

In this paper, a compact broadband planar inverted-F antenna (PIFA) with dual-resonant modes (TM1/2,2 and TM3/2,0) is proposed for 5G applications. By loading a pair of horizontal slots on the patch, the TM3/2,0 mode can be shifted downward and combined with the TM1/2,2 mode, leading to a dual-mode operation. Meanwhile, another pair of slots, which are orthogonal to the previous pair, is introduced to improve the impedance matching of the antenna. Moreover, the substrate with a high dielectric constant is used in this design to achieve a compact antenna size. In order to verify the principle and the design method, an antenna prototype was fabricated and measured. Experimental results show that the PIFA has a good performance with a −10 dB impedance bandwidth of 14.5% (3.17–3.67 GHz), a peak gain of 6.23 dBi, a low cross-polarization level of −17.3 dB, and a compact size of 0.45 × 0.26 × 0.03 λ013 (λ01 is the free-space wavelength at 3.5 GHz). The antenna is predicted to be suitable for 5G terminal applications.
Meaning of the Decreased HPV Normalized Viral Load Marker in Clinical Evolution of Women with HPV Infection
Authors: Rojo-Alba Susana , Álvarez-Argüelles Marta Elena , Ruano Yolanda , Pérez-Martinez Zulema , Boga Jose Antonio , De Oña María , Palacio Ana , Solares María Concepción , Melón Santiago
Published: September 2022

(1) Background: HPV infection can progress over the years to become cervical cancer. In this study, genotype and a normalized viral load were evaluated as surrogate markers of progression to cancer. (2) Methods: A total of 558 endocervical swabs were collected from 120 women (mean, 40.1 ± 11.8 years old). Seventy-eight of the women underwent clinical intervention (CI) to clear the infection during the course of the study, while forty-two did not (NCI). Normalized viral load (NVL) was calculated using a COBAS 4800 system. The INNOLIPA genotyping system was used to classify HPV which was neither type 16 or 18. (3) Results: The mean age of CI women was 41.1 ± 11.4 (22–68) years old and that of the NCI group was 37.7 ± 12.13 (23–65) (p: 0.104). HPV16 was present in 11 (25%) NCI and 30 (35.2%) CI patients, HPVα9non16 in 20 (45%) NCI and 34 (40%) CI, and HPVnonα9 in 13 (29.5%) NCI and 21 (24.7%) CI (p = 0.48). In NCI women there was an average NVL decrease of 0.95 log after two years and a further decrease of 2.35 log at the end of the third year. At the end of the study, 34 (80%) of the NCI patients were clear of HPV. However, NVL of CI women remained at around 5 log until intervention (p < 0.001). (4) Conclusions: Viral load decreased in NCI women at follow-up in the second year. In contrast, in CI women, their viral load did not fall over the follow-up period. This work thus demonstrates that a reduction in normalized viral load was associated with good evolution.
Reduced-Precision Chemical Kinetics in Atmospheric Models
Authors: Sophocleous Kyriacos , Christoudias Theodoros
Published: September 2022

Modelling atmospheric composition and climate change on the global scale remains a great scientific challenge. Earth system models spend up to 85% of their total required computational resources on the integration of atmospheric chemical kinetics. We refactored a general atmospheric chemical kinetics solver system to maintain accuracy in single precision to alleviate the bottleneck in memory-limited climate-chemistry simulations and file input/output (I/O) and introduced vectorisation by intrinsic functions to increase data-level parallelism exposure. The application was validated using seven standard chemical mechanisms and evaluated against high-precision implicit methods. We reduced required integration steps by ×1.5–3-fold, in line with double precision, while maintaining numerical stability under the same conditions, accuracy to within 1%, and benefiting from halving the required memory and reducing overall simulation time by up to a factor two. Our results suggest single-precision chemical kinetics can allow significant reduction of computational requirements and/or increase of complexity in climate-chemistry simulations.
Tropical Cyclone Exposure in the North Indian Ocean
Authors: Kabir Rubaiya , Ritchie Elizabeth A. , Stark Clair
Published: September 2022

The North Indian Ocean is a region with a high coastal population and a low-lying delta, making it a high-risk region for tropical cyclone impacts. A 30-year period from 1989–2018 has been used to examine the TC landfalling exposure in the North Indian Ocean and its changes by considering 30 years of IBTrACs data, ERA5 atmospheric data, and 20 years of TRMM and DAV data. A total of 185 TCs made landfall in the NIO during the 30-year period with the majority of the TCs making landfall during the pre- and post-monsoon seasons. Rainfall associated with landfalling TCs decreased in the last 10 years of analysis (2009–2018) compared to the first 10 years of available data from 1999–2008. During the monsoon, TC activity is relatively lower compared to the post-monsoon periods, even though higher accumulated TC-associated rainfall typically occurs during the monsoon period, particularly along the eastern coastlines of the Arabian Sea and the Bay of Bengal. The TC winds impact most of the Bay of Bengal coastline, including Sri Lanka. The spatial distribution of landfalling TCs changes with the season, with most of the landfalling activity occurring during the pre- and post-monsoon periods. Interestingly, more recent TC activity has shifted to the northeast India and Bangladesh coasts, suggesting that these regions may be more vulnerable to TC impacts in the future.
Population and GDP Exposure to Extreme Precipitation Events on Loess Plateau under the 1.5 °C Global Warming Level
Authors: Ta Zhijie , Li Kaiyu , Han Hongzhu , Jin Qian
Published: September 2022

To mitigate the adverse effects of climate warming, the Paris Agreement proposed the goal to reduce global warming up to an increase of 1.5 °C above the preindustrial level. Study of the population and GDP exposure to precipitation extreme events under the 1.5 °C warming target is fundamental for disaster risk mitigation and adaptation on the Loess Plateau. This study projected the population and GDP exposure to extreme precipitation events under the 1.5 °C global warming level on the Loess Plateau using daily precipitation data from CMIP6 outputs and population and GDP data under a Shared Socioeconomic Pathway 1(SSP1) 2.6 scenario. The population and GDP exposure were evaluated by combing the frequency and the areal coverage of the extreme precipitation events. Results show that population and GDP exposure to extreme precipitation events on the Loess Plateau will increase under the 1.5 °C global warming level. The population exposure was projected from 1.32 × 106 to 2.68 × 106 person-year. The population exposure of eastern and southern Loess Plateau is significantly higher than that of the northern region. The annual exposure of GDP ranges from USD 2.9 to 12.3 billion, and the regions with the highest GDP exposure are Zhengzhou, Xi’an, Taiyuan, and Lanzhou. Our results reveal that limiting the increase of global mean temperature to 1.5 °C warming level is of great significance to reduce the social and economic exposure to extreme precipitation events on the Loess Plateau.
Analysis of Atmospheric Pollutants and Meteorological Factors on PM2.5 Concentration and Temporal Variations in Harbin
Authors: Gao Xiuyan , Ruan Zhaohui , Liu Jiemei , Chen Qixiang , Yuan Yuan
Published: September 2022

With rapid economic development, the problem of air pollution has become increasingly prominent. Countries have paid attention to PM2.5, one of the main air pollutants, and have gradually addressed this issue. Based on the 2015–2019 air quality data, meteorological data, and aerosol optical depth data from Harbin, China, this study investigated the relationship between PM2.5, a number of influencing factors, and their temporal changes using a machine-learning method. It can be seen from the analysis that the random forest model can predict PM2.5 concentration. In this model, the mean RH and AOD have a high impact on PM2.5 concentration, but there was negligent correlation with PM2.5. The results indicated that the level of PM2.5 pollution continuously decreased from 2015 to 2019, and there were significant seasonal differences in PM2.5 concentration and its variations. In 2019, due to the impact of heating and adverse meteorological conditions, PM2.5 pollution during the heating period increased significantly. This study provides theoretical and data support for the analysis of PM2.5 pollution in Harbin and formulation of air pollution control policies.
Impacts of Multi-Source Microwave Satellite Radiance Data Assimilation on the Forecast of Typhoon Ampil
Authors: Shu Aiqing , Xu Dongmei , Zhang Shiyu , Shen Feifei , Zhang Xuewei , Song Lixin
Published: September 2022

This study investigates the impacts of the joint assimilation of microware temperature sensor, Advanced Microwave Sounding Unit-A (AMSUA), and microware humidity sensors, Microwave Humidity Sounder (MHS) and Microwave Humidity Sounder-2 (MWHS2), on the analyses and forecasts for the tropical cyclone (TC) system. Experiments are conducted using a three-dimensional variation (3DVAR) algorithm in the framework of the weather research and forecasting data assimilation (WRFDA) system for the forecasting of Typhoon Ampil (2018). The results show that the assimilation of MWHS2 radiance data improves the analyses better in terms of TC’s structure and moisture conditions than those of the MHS experiment. To some extent, the experiment with only AMSUA radiance delivers some positive impacts of the precipitation, track, and intensity forecast than the other two experiments do. In addition, the skill of the precipitation forecast is notably enhanced with higher equitable threat score (ETS) by the simultaneous assimilation of the MHS, MWHS2, and AMSUA radiance. Generally, assimilation of radiance from all sources of MHS, MWHS2, and AMSUA could combine the advantages of assimilating each type of sensors rather than individually. The consistent improvement is also confirmed for the TC’s track forecast with reduced error on average, whereas the improvement of intensity forecast is not obvious.
Closing the Feedback of Evapotranspiration on the Atmospheric Evaporation Demand Based on a Complementary Relationship
Authors: Li Tongtong , Liu Dengfeng , Han Songjun , Ming Guanghui , Fan Jingjing , Meng Xianmeng , Huang Qiang
Published: September 2022

Evapotranspiration is the important feedback of the catchment into the atmosphere. However, in catchment hydrological modeling, the feedback of evaporation into the atmosphere is not closed and potential evaporation is always a meteorological forcing which is not dependent on the actual evaporation. A modeling framework to close the feedback of evapotranspiration into the atmosphere (FCEA) based on the evapotranspiration complementary relationship was proposed in the catchment hydrological modeling, and the effect of land-use changes on the runoff and evapotranspiration in the upper reach of Han River of China was investigated in the FCEA. Brutsaert uses the boundary condition analysis method to propose a nonlinear complementary relationship based on polynomial formula (B2015 function), which was applied in the study area, and the parameters were calibrated based on the catchment water balance of 1972–1990 and validated in 1991–2017. The actual evapotranspiration (AET) in the study area was estimated based on the complementary model in the upper reach of Han River. The SWAT model was used to simulate the catchment hydrological processes in the study area from 1972 to 2017. The evapotranspiration in the upper reach of Han River was studied in four scenarios to realize the feedback of evapotranspiration to the atmosphere and analyze the impact of the evapotranspiration feedback to the change of runoff in the basin. The results showed that the annual runoff in the upper reach of the Han River will increase, and the annual actual evapotranspiration will decrease in the long-term simulations in Scenarios 1 and 4. In Scenarios 2 and 3, with the increase of woodland, the annual runoff will decrease due to the feedback to the atmosphere, and annual actual evapotranspiration will increase, which is related to the increase in ecological water demand caused by the increase in woodland. Converting grassland into farmland will increase the runoff of the watershed. It is important to improve the land-use planning policy in the Han River Basin in order to realize the sustainable development of the river basin.
Development of a Fusion Framework for Lithium-Ion Battery Capacity Estimation in Electric Vehicles
Authors: Jiang Bo , Wei Xuezhe , Dai Haifeng
Published: September 2022

The performance of a battery system is critical to the development of electric vehicles (EVs). Battery capacity decays with the use of EVs and an advanced onboard battery management system is required to estimate battery capacity accurately. However, the acquired capacity suffers from poor accuracy caused by the inadequate utilization of battery information and the limitation of a single estimation method. This paper investigates an innovative fusion method based on the information fusion technique for battery capacity estimation, considering the actual working conditions of EVs. Firstly, a general framework for battery capacity estimation and fusion is proposed and two conventional capacity estimation methods running in different EV operating conditions are revisited. The error covariance of different estimations is deduced to evaluate the estimation uncertainties. Then, a fusion state–space function is constructed and realized through the Kalman filter to achieve the adaptive fusion of multi-dimensional capacity estimation. Several experiments simulating the actual battery operations in EVs are designed and performed to validate the proposed method. Experimental results show that the proposed method performs better than conventional methods, obtaining more accurate and stable capacity estimation under different aging statuses. Finally, a practical judgment criterion for the current deviation fault is proposed based on fusion capacity.