bluuebunny/crossref_metadata_2025 huggingface dataset:
Design and Verification of Short-Distance Landing Control System for a One-Third-Scale Unmanned Supersonic Experimental Airplane
Authors: Hyokawa Satoshi , Ueba Masazumi
Published: March 2023

The Aerospace Plane Research Center at the Muroran Institute of Technology is currently conducting research to develop enabling technologies for high-speed aircraft traveling at high altitudes and constructing experimental, small-scale, unmanned supersonic aircraft called Oowashi as a testbed for flight. To confirm the control performance of the aircraft, an experiment using a one-third-scale model of the Oowashi aircraft has been planned. The flight of high-speed aircraft always presents the problem of having to land on an ordinary runway regardless of the aircraft’s high speed at the beginning of the landing process. This paper therefore proposes a new landing control design method that can shorten the landing distance for a high-speed aircraft without increasing the rate of descent. The design method utilizes the newly clarified relationship between an angle of attack and the time constant of flare control system, which is effective to raise glideslope angle during landing. The validity of the method is confirmed by computer simulation assuming the model aircraft equivalent to a one-third-scale model of the Oowashi aircraft.
Citrus Disease Image Generation and Classification Based on Improved FastGAN and EfficientNet-B5
Authors: Dai Qiufang , Guo Yuanhang , Li Zhen , Song Shuran , Lyu Shilei , Sun Daozong , Wang Yuan , Chen Ziwei
Published: March 2023

The rapid and accurate identification of citrus leaf diseases is crucial for the sustainable development of the citrus industry. Because citrus leaf disease samples are small, unevenly distributed, and difficult to collect, we redesigned the generator structure of FastGAN and added small batch standard deviations to the discriminator to produce an enhanced model called FastGAN2, which was used for generating citrus disease and nutritional deficiency (zinc and magnesium deficiency) images. The performance of the existing model degrades significantly when the training and test data exhibit large differences in appearance or originate from different regions. To solve this problem, we propose an EfficientNet-B5 network incorporating adaptive angular margin (Arcface) loss with the adversarial weight perturbation mechanism, and we call it EfficientNet-B5-pro. The FastGAN2 network can be trained using only 50 images. The Fréchet Inception Distance (FID) and Kernel Inception Distance (KID) are improved by 31.8% and 59.86%, respectively, compared to the original FastGAN network; 8000 images were generated using the FastGAN2 network (2000 black star disease, 2000 canker disease, 2000 healthy, 2000 deficiency). Only images generated by the FastGAN2 network were used as the training set to train the ten classification networks. Real images, which were not used to train the FastGAN2 network, were used as the test set. The average accuracy rates of the ten classification networks exceeded 93%. The accuracy, precision, recall, and F1 scores achieved by EfficientNet-B5-pro were 97.04%, 97.32%, 96.96%, and 97.09%, respectively, and they were 2.26%, 1.19%, 1.98%, and 1.86% higher than those of EfficientNet-B5, respectively. The classification network model can be successfully trained using only the images generated by FastGAN2, and EfficientNet-B5-pro has good generalization and robustness. The method used in this study can be an effective tool for citrus disease and nutritional deficiency image classification using a small number of samples.
The Influence of Selected Factors on the Nutritional Value of the Milk of Cold-Blooded Mares: The Example of the Sokólski Breed
Authors: Barłowska Joanna , Polak Grażyna , Janczarek Iwona , Tkaczyk Ewelina
Published: March 2023

This study assessed the effect of access to pasture, lactation number, and foals’ sex on the nutritional value of milk (79 samples) from nine mares. The following were analysed: content of dry matter, protein, fat, lactose, and ash; percentages of α-lactalbumin (α-La), β-lactoglobulin (β-Lg), serum albumin (SA), immunoglobulins (Ig), lactoferrin (Lf), and lysozyme (Lz) in the total protein; and the fatty acid profile. Mares without access to pastures were shown to produce milk with a higher dry matter content, including fat, lactose, and ash; higher percentages of β-Lg, α-La, Ig, and Lf; and a better fatty acid profile. The milk from mares with access to pasture contained more protein, including higher percentages of SA and Lz. Milk from mares in lactations 4–6 had the highest fat and protein concentrations and the lowest lactose concentration. The α-La level was highest in lactation 1, Lf in lactations 2–3, and Lz in lactations 4–6. Milk from mares in lactations 4–6 had the best fatty acid profile (the lowest concentration of saturated fatty acids (SFAs) and the highest concentration of monounsaturated fatty acids(MUFA) and polyunsaturated fatty acids (PUFA)). Milk from mothers of female offspring had higher dry matter, fat, and protein concentrations, a higher share of lysozyme, and a better fatty acid profile.
Ecosystem Conditions That Influence the Viability of an Old-Forest Species with Limited Vagility: The Red Tree Vole
Authors: Gaines William L. , Lyons Andrea L. , Suring Lowell H. , Hughes Carol S.
Published: March 2023

We evaluated ecosystem conditions known to influence the viability of a strictly arboreal species (the red tree vole, Arborimus longicaudus) endemic and historically distributed in the forests across the Coast Range, Cascades, and Klamath Mountains ecoregions in the Western United States of America. We found widespread reductions in ecosystem conditions needed to support the long-term viability of the red tree vole. This was particularly evident in the Coast Range where the weighted watershed index (WWI) was 26% of its historical value, and the current probability of maintaining viability departed the most from historical viability probabilities in ecoregions that were evaluated. In contrast, in the Cascades and Klamath Mountains, the WWI was 42% and 52% of their respective historical values, and the current probabilities of maintaining viability departed less from historical conditions than in the Coast Range. Habitat loss from timber harvest represented the most immediate threat in the Coast Range, while habitat loss from wildfires represented the most risk to the red tree vole in the Cascades and Klamath Mountains. Reducing the risks to the viability of the red tree vole will depend largely on the implementation of conservation practices designed to protect remaining habitat and restore degraded ecosystems in the Coast Range. However, the risk of large, high-severity wildfires will require the protection and increased resilience of existing ecosystems. Our results indicate that considerable adaptation to climate change will be required to conserve the red tree vole in the long term. Conservation may be accomplished by revising land and resource management plans to include standards and guidelines relevant to red tree vole management and persistence, the identification of priority areas for conservation and restoration, and in assessing how management alternatives influence ecosystem resiliency and red tree vole viability.
Brain-Derived Neurotrophic Factor, Kynurenine Pathway, and Lipid-Profiling Alterations as Potential Animal Welfare Indicators in Dairy Cattle
Authors: Favole Alessandra , Testori Camilla , Bergagna Stefania , Gennero Maria Silvia , Ingravalle Francesco , Costa Barbara , Barresi Sara , Curti Piercarlo , Barberis Francesco , Ganio Sandra , Orusa Riccardo , Vallino Costassa Elena , Berrone Elena , Vernè Marco , Scaglia Massimo , Palmitessa Claudia , Gallo Marina , Tessarolo Carlotta , Pederiva Sabina , Ferrari Alessio , Lorenzi Valentina , Fusi Francesca , Brunelli Laura , Pastorelli Roberta , Cagnotti Giulia , Casalone Cristina , Caramelli Maria , Corona Cristiano
Published: March 2023

Complete animal welfare evaluation in intensive farming is challenging. With this study, we investigate new biomarkers for animal physical and mental health by comparing plasma expression of biochemical indicators in dairy cows reared in three different systems: (A) semi-intensive free-stall, (B) non-intensive tie-stall, and (C) intensive free-stall. Additionally, protein levels of mature brain-derived neurotrophic factor (mBDNF) and its precursor form (proBDNF) and indoleamine 2,3-dioxygenase (IDO1) specific activity were evaluated in brain samples collected from 12 cattle culled between 73 and 138 months of age. Alterations in plasma lipid composition and in the kynurenine pathway of tryptophan metabolism were observed in the tie-stall-reared animals. The total plasma BDNF concentration was higher in tie-stall group compared to the two free-housing groups. Brain analysis of the tie-stall animals revealed a different mBDNF/proBDNF ratio, with a higher level of proBDNF (p < 0.001). Our data are similar to previous studies on animal models of depression, which reported that inhibition of the conversion of proBDNF in its mature form and/or elevated peripheral kynurenine pathway activation may underlie cerebral biochemical changes and induce depressive-like state behavior in animals.
Information Theory Opens New Dimensions in Experimental Studies of Animal Behaviour and Communication
Authors: Reznikova Zhanna
Published: March 2023

Over the last 40–50 years, ethology has become increasingly quantitative and computational. However, when analysing animal behavioural sequences, researchers often need help finding an adequate model to assess certain characteristics of these sequences while using a relatively small number of parameters. In this review, I demonstrate that the information theory approaches based on Shannon entropy and Kolmogorov complexity can furnish effective tools to analyse and compare animal natural behaviours. In addition to a comparative analysis of stereotypic behavioural sequences, information theory can provide ideas for particular experiments on sophisticated animal communications. In particular, it has made it possible to discover the existence of a developed symbolic “language” in leader-scouting ant species based on the ability of these ants to transfer abstract information about remote events.
The Impact of Visitors on Non-Primate Species in Zoos: A Quantitative Review
Authors: Williams Ellen , Hunton Violet , Hosey Geoff , Ward Samantha J.
Published: March 2023

Visitors are a prominent feature in the lives of zoo animals, and their presence can cause a range of impacts on zoo animals (typically classed as positive, negative or neutral impacts), commonly referred to as the ‘visitor effect’. This paper quantitatively collates the literature on the visitor effect in non-primate species, investigates the types of measures used to assess impacts of visitors on animals and considers whether impacts vary across non-primate species in zoos. In total, there were 105 papers which had investigated the impact of zoo visitors on 252 non-primate species/species groups. There has been a steady increase in visitor effect research in zoos since 2012 and this body of work incorporates species from avian (28% study species), reptilian (9%), amphibian (2%), fish (4%) and invertebrate taxa (1%). However, there is still a bias towards mammalian species (56%). The response to visitors varied across taxa. Amphibians responded negatively to visitors more frequently than would be expected by chance (p < 0.05), birds responded neutrally more frequently than would be expected by chance (p < 0.05) and fish responded neutrally and ‘unknown’ more frequently than would be expected by chance (p < 0.05). This review highlighted a number of animal-based metrics which have been used to assess the impacts of visitors on animals, with measures used varying across taxa. Moving forwards, it is recommended that moving forwards researchers incorporate a suite of measures, incorporating those which are meaningful in terms of being representative of individual animal experiences and animal welfare, collected in a manner which should capture those metrics accurately.
Anti-Inflammation and Anti-Melanogenic Effects of Maca Root Extracts Fermented Using Lactobacillus Strains
Authors: Yang Jisun , Cho Hyeijin , Gil Minchan , Kim Kyung Eun
Published: March 2023

Maca is a well-known biennial herb with various physiological properties, such as antioxidant activity and immune response regulation. In this study, the antioxidant, anti-inflammatory, and anti-melanogenic effects of fermented maca root extracts were investigated. The fermentation was carried out using Lactobacillus strains, such as Lactiplantibacillus plantarum subsp. plantarum, Lacticaseibacillus rhamnosus, Lacticaseibacillus casei, and Lactobacillus gasseri. In RAW 264.7 cells, the non-fermented maca root extracts increased the secretion of nitric oxide (NO), an inflammatory mediator, in a dose-dependent manner. In contrast, the fermented extracts showed considerably lower NO secretion than the non-fermented extracts at concentrations of 5% and 10%. This indicates the effective anti-inflammatory effects of fermented maca. The fermented maca root extracts also inhibited tyrosinase activity, melanin synthesis, and melanogenesis by suppressing MITF-related mechanisms. These results show that fermented maca root extracts exhibit higher anti-inflammatory and anti-melanogenesis effects than non-fermented maca root extracts. Thus, maca root extracts fermented using Lactobacillus strains have the potential to be used as an effective cosmeceutical raw material.
Antioxidant Activity and Inhibition of Digestive Enzymes of New Strawberry Tree Fruit/Apple Smoothies
Authors: Gil Katarzyna Angelika , Nowicka Paulina , Wojdyło Aneta , Serreli Gabriele , Deiana Monica , Tuberoso Carlo Ignazio Giovanni
Published: March 2023

In this study, original smoothies obtained with strawberry tree fruit puree and apple juice enriched with Diospyros kaki fruits, Myrtus communis purple berry extract, Acca sellowiana, and Crocus sativus petal juice were evaluated for their antioxidant activity and inhibition of targeted digestive enzymes. Values of CUPRAC, FRAP, ORAC, DPPH•, and ABTS•+ assays generally increased with plant enrichment, particularly for A. sellowiana addition (ABTS•+ 2.51 ± 0.01 mmol Trolox/100 g fw). The same trend was observed regarding the ability to scavenge reactive oxygen species (ROS) tested in Caco-2 cell cultures. Inhibitory activity on α-amylase and α-glucosidase was increased by D. kaki, M. communis, and A. sellowiana. Total polyphenols evaluated by UPLC-PDA analysis ranged between 535.75 ± 3.11 and 635.96 ± 5.21 mg/100 g fw, and A. sellowiana provided the higher amount. Flavan-3-ols accounted for more than 70% of phenolic compounds, and only smoothies enriched with C. sativus showed a high amount of anthocyanins (25.12 ± 0.18 mg/100 g fw). The outcome of this study indicates these original smoothies as a possible ally in counteracting oxidative stress, as established by their favourable antioxidant compound profile, thus suggesting an interesting future application as nutraceuticals.
Rich Dynamics of a General Producer–Grazer Interaction Model under Shared Multiple Resource Limitations
Authors: Phan Tin , Elser James J. , Kuang Yang
Published: March 2023

Organism growth is often determined by multiple resources interdependently. However, growth models based on the Droop cell quota framework have historically been built using threshold formulations, which means they intrinsically involve single-resource limitations. In addition, it is a daunting task to study the global dynamics of these models mathematically, since they employ minimum functions that are non-smooth (not differentiable). To provide an approach to encompass interactions of multiple resources, we propose a multiple-resource limitation growth function based on the Droop cell quota concept and incorporate it into an existing producer–grazer model. The formulation of the producer’s growth rate is based on cell growth process time-tracking, while the grazer’s growth rate is constructed based on optimal limiting nutrient allocation in cell transcription and translation phases. We show that the proposed model captures a wide range of experimental observations, such as the paradox of enrichment, the paradox of energy enrichment, and the paradox of nutrient enrichment. Together, our proposed formulation and the existing threshold formulation provide bounds on the expected growth of an organism. Moreover, the proposed model is mathematically more tractable, since it does not use the minimum functions as in other stoichiometric models.
A Mixed Clustering Approach for Real-Time Anomaly Detection
Authors: Mazarbhuiya Fokrul Alom , Shenify Mohamed
Published: March 2023

Anomaly detection in real-time data is accepted as a vital area of research. Clustering techniques have effectively been applied for the detection of anomalies several times. As the datasets are real time, the time of data generation is important. Most of the existing clustering-based methods either follow a partitioning or a hierarchical approach without addressing time attributes of the dataset distinctly. In this article, a mixed clustering approach is introduced for this purpose, which also takes time attributes into consideration. It is a two-phase method that first follows a partitioning approach, then an agglomerative hierarchical approach. The dataset can have mixed attributes. In phase one, a unified metric is used that is defined based on mixed attributes. The same metric is also used for merging similar clusters in phase two. Tracking of the time stamp associated with each data instance is conducted simultaneously, producing clusters with different lifetimes in phase one. Then, in phase two, the similar clusters are merged along with their lifetimes. While merging the similar clusters, the lifetimes of the corresponding clusters with overlapping cores are merged using superimposition operation, producing a fuzzy time interval. This way, each cluster will have an associated fuzzy lifetime. The data instances either belonging to sparse clusters, not belonging to any of the clusters or falling in the fuzzy lifetimes with low membership values can be treated as anomalies. The efficacy of the algorithms can be established using both complexity analysis as well as experimental studies. The experimental results with a real world dataset and a synthetic dataset show that the proposed algorithm can detect the anomalies with 90% and 98% accuracy, respectively.
Application Research of Negative Pressure Wave Signal Denoising Method Based on VMD
Authors: Jiang Zhu , Guo Ganghui , Liu Boxiang
Published: March 2023

The quality of pipeline leakage fault feature extractions deteriorates due to the influence of fluid pipeline running state and signal acquisition equipment. The pressure signal is characterized by high complexity, nonlinear and strong correlation. Therefore, traditional denoising methods have difficulty dealing with this kind of signal. In order to realize accurate leakage fault alarm and leak location, a denoising method based on variational mode decomposition (VMD) technology is proposed in this paper. Firstly, the intrinsic mode functions are screened out using the correlation coefficient. Secondly, information entropy is used to optimize the VMD decomposition layers k. Finally, based on the denoising signal, the inflection point of the negative pressure wave is extracted, and the position of the leakage point is calculated according to the time difference between the two inflection points. To verify the effectiveness of the algorithm, both laboratory experiments and real pipeline tests are conducted. Experimental results show that the method proposed by this paper can be used to effectively denoise the pressure signal. Furthermore, from the perspective of positioning accuracy, compared other methods, the proposed method can achieve a better positioning effect, as the positioning accuracy of the laboratory experiment reaches up to 0.9%, and that of the real pipeline test leakage point reaches up to 0.41%.
Effectiveness of Protein and Polysaccharide Biopolymers as Dust Suppressants on Mine Soils: Results from Wind Tunnel and Penetrometer Testing
Authors: Sieger Johannes L. , Lottermoser Bernd G. , Freer Justus
Published: March 2023

For the dust control of barren mine soils, protein and polysaccharide biopolymers have recently shown potential as environmentally friendly alternatives to conventional dust suppressants (e.g., salt brines or petroleum-based products). However, laboratory studies that determine suitable application parameters are required for large-scale field trials. This study performed wind tunnel and pocket penetrometer tests to investigate the wind erosion and penetration resistance of treatments with different biopolymer types, concentrations (wt%), and application rates (L/m2) on two mine soils. The results demonstrate that all treatments significantly enhanced the wind erosion resistance of both tested soil types, with the biopolymer type, concentration, and application rate having a significant effect. Depending on the biopolymer type and application parameter, the wind-induced soil loss ranged from 0.86 to 423.9 g/m2 (Control = 2645.0 g/m2) for medium-grained sand and from 0.3 to 225 g/m2 (Control = 26,177.0 g/m2) for fine-grained silica sand, with the soil loss reducing as concentrations increase, until it reached a plateau concentration. For a similar performance, the tested proteins (wheat and fava bean protein) must be applied at higher concentrations than those of the polysaccharides (xanthan gum, corn starch, and carboxymethylcellulose). Spearman rank correlation revealed a moderate-to-strong negative correlation between soil loss (g/m2) and penetration resistance (N), rendering the pocket penetrometer a rapid, low-cost, and indirect method for evaluating potential dust suppressants. This research contributes to evaluating biopolymers as alternatives to traditional dust suppressants for controlling dust emissions on barren surfaces. Biopolymers are biodegradable and can be sourced regionally at a relatively low cost, reducing the environmental impact and expenses associated with dust suppression.
Speed Limit of Linear Induction Motor Subway Trains Running through 65 m Radius Curves on Yard Line
Authors: Zhou Qing , Wang Jianuo , Han Jian , Jin Xuesong
Published: March 2023

Linear induction motor (LIM) subway yard line often have very-small-radius curves and small turnouts with “S”-shaped curves in the middle. The lateral stability of the train is low, and wheel-climb (slipway) derailments often occur at a speed of 10 km/h. To study the derailment safety and speed limit of a linear motor subway train running through yard line, a coupling dynamic model of the train-track system is established, fully considering the driving characteristics of the linear motor, characteristics of the linear motor train, and track structure. The safety of train derailment is judged by the over-limit time of the derailment coefficient. Under the premise of a safe operation, the variations in the derailment coefficient, out-of-limit time, wheel unloading rate, and wheel-axle lateral force with the train running speed are studied. When the train runs at speeds below 25 km/h, for both new and worn rails, the derailment coefficient and lateral force of the wheel axle at each speed exceed the safety limits, and are less affected by changes in the speed. The duration of the derailment coefficient is within the safety limit because the speed of crossing the curve is low, and thus the train will not overturn and derail. Rail wear reduces the train derailment safety through the yard line, while the wheel wear improves the train derailment safety through the yard line. Considering the actual state of the yard line (wheel-rail wear, irregularity, etc.), the speed of the linear motor subway train running through the yard line should be limited to below 15 km/h.
Dynamic Analysis of Underwater Torpedo during Straight-Line Navigation
Authors: Zhao Bowen , Sun Jiyuan , Zhang Dapeng , Zhu Keqiang , Jiang Haoyu
Published: March 2023

Torpedoes play an irreplaceable role in naval warfare; therefore, it is significant to study the dynamic response of the direct navigation of torpedoes. In order to study the dynamic response of torpedoes under different Munk moment coefficients, the dynamic equation of torpedoes is established based on the momentum theorem and the momentum moment theorem. The linear motion mathematical model of torpedoes is obtained. The relationship between the torpedo and the Munk moment coefficient is derived. The straight-line motion model of the torpedo under different Munk moments is established, and the dynamic properties of the space motion of the torpedo are analyzed. It is found that the Munk moment coefficient increase will lead to an increase in the deflection of the torpedo’s direct motion on each degree of freedom, and the Munk moment coefficient is related to the additional mass matrix. During the design of the torpedo, the added mass should be reduced by changing the shape of the torpedo as much as possible so as to reduce the pitch moment, yaw, and roll moments of the torpedo.
Using Historical Data to Dynamically Route Post-Disaster Assessment Unmanned Aerial Vehicles in the Context of Responding to Tornadoes
Authors: Grogan Sean , Gamache Michel , Pellerin Robert
Published: March 2023

Responding to tornado disasters resides at a unique intersection of search and rescue operations: it has attributes of wilderness and maritime search and rescue operations and search and rescue operations in the aftermath of earthquakes and hurricanes. This paper presents a method of attempting to leverage historical data to more efficiently identify the extent of the area damaged by a tornado. To assist in building and understanding the historical data, we also develop a method to generate tornado areas that react similarly to the limited historical data set. The paper successfully demonstrates the method of creating artificial tornado instances that can be used as a testing sandbox for the further development of tools when responding to tornado-type disasters. These artificial instances perform similarly in some important metrics to the historical database of tornado instances that we produced. This paper also shows that the use of historical tornado trends has an impact on the response method outlined in this article, typically reducing the standard deviation of the time it takes to fully identify the extent of the damage.
Aquatic Macrophyte Biomass Periodically Harvested Form Shipping Routes and Drainage Systems in a Selected Region of Poland as a Substrate for Biogas Production
Authors: Dębowski Marcin , Zieliński Marcin , Kazimierowicz Joanna , Walery Maria
Published: March 2023

One of the identified obstacles to the development of biogas plants is the limited sources of organic substrates. Hydrophytes varying in morphology, chemical composition, and origin proved to be viable alternatives. This study’s aim was to determine the feasibility of deploying biomass from the cleansing of water reservoirs for anaerobic digestion. A mass and energy balance was estimated for Warmia–Mazury Province (Poland), the so-called Thousand Lake District. The effectiveness of anaerobic digestion was determined in anaerobic batch respirometric reactors. The biomass of hydrophytes harvested from this area approximated 38,070 Mg FM/year. The biogas yield from emergent plants approximated 350 m3/MgVS, and the average CH4 content of biogas reached 55%, whereas the respective values obtained from submerged biomass reached 270 m3/MgVS and 58% CH4. The total CH4 volume achievable from the facility fed with waste biomass of this type allows producing ca. 1,654,560 m3CH4/year, which enables reaching 866 kW theoretical thermal power and 636 kWe net electrical power with the facility. The contribution of biomass from mowing in this energy effect was about 84%, whereas that of the submerged vegetation obtained by hacking the bottom was 16%.
The Effect of Expanded Glass and Crushed Expanded Polystyrene on the Performance Characteristics of Lightweight Concrete
Authors: Šeputytė-Jucikė Jurga , Vėjelis Sigitas , Kizinievič Viktor , Kairytė Agnė , Vaitkus Saulius
Published: March 2023

This paper describes the production and performance characteristics of lightweight concrete (LWC) made from porous aggregates, such as expanded glass (EG), made from glass waste, and crushed expanded polystyrene waste (CEPW), obtained by crushing packaging waste from household appliances and ordinary Portland cement (OPC). During the study, the LWC density, thermal conductivity, compressive strength, bending strength, water absorption, deformations, composite structure, and freeze–thaw resistance were evaluated. By changing the amount of OPC and replacing part of the EG with CEPW, it was possible to reduce the thermal conductivity from 0.0977 to 0.0720 W/(mK). The presence of CEPW did not degrade compressive and bending strength or long-term water absorption of LWC. The influence of the amount of porous aggregates and OPC on the resistance to freezing and thawing was investigated by two methods. In one case, the freezing resistance was studied by the method of one-sided freezing of LWC structural indicators and, in the other case, the freezing resistance was determined by the decrease in compressive strength after 25, 100, and 200 freeze–thaw cycles. By modifying the structure with CEPW aggregate the durability of LWC products was increased and deformations were decreased.
Simulation Research on the Grouser Effect of a Reconfigurable Wheel-Crawler Integrated Walking Mechanism Based on the Surface Response Method
Authors: Zhou Pengfei , Tang Shufeng , Sun Zaiyong
Published: March 2023

To improve the unstructured terrain traversing performance of the scientific research robot of the Qinghai–Tibet Plateau station, the parameters of the track shoe of the reconfigurable wheel-crawler walking mechanism were studied. Based on a typical track shoe puncture effect model, the experimental design was carried out based on the surface response method, and the dynamic model of the triangular crawler mode of the reconfigurable wheel-crawler walking mechanism was constructed and tested using RecurDyn V9R3 software. Through an analysis of the simulation results, the interaction of the grouser parameters was further clarified, and the regression equation of the traction force of the walking mechanism was obtained. The grouser parameters that enabled the reconfigurable wheel-crawler walking mechanism to have the maximum traction were obtained; these will be used to guide the machining of the prototype walking mechanism.
Improving Structural Performance of Reinforced Concrete Beams with Phragmites Australis Fiber and Waste Glass Additives
Authors: Ramadan Rawan , Jahami Ali , Khatib Jamal , El-Hassan Hilal , Elkordi Adel
Published: March 2023

The construction industry has seen a growing emphasis on the use of sustainable materials in recent years. This is driven by various factors, including a desire to reduce environmental impact, improve indoor air quality, and promote the health and well-being of building occupants. One sustainable material that is being increasingly utilized in construction is natural fibers. Phragmites australis fibers, in particular, are renewable, biodegradable, and have a low carbon footprint. The present study aims to evaluate the impact of Phragmites australis fibers on the behavior of reinforced concrete beams. Five concrete mixes were utilized in the experiment, with the control mix having a 1:1.5:3 ratio of cement to sand to coarse aggregate by weight. The other four mixes incorporated Phragmites australis fibers at 0%, 0.5%, 1%, and 1.5% of the volume of the mix, with cement replaced by 10% glass by weight. The water-to-cement ratio was set at 0.4 for all mixes. Concrete cubes, cylinders, and prisms were prepared to determine mechanical and physical properties, while reinforced concrete beams were used to assess structural performance. The results of the experiment showed that the addition of Phragmites australis fibers slightly decreased the compressive and tensile strength of the concrete compared to the control mix. However, the inclusion of 0.5% Phragmites australis fibers enhanced the split tensile and flexural strength of the concrete. In terms of reinforced concrete beams, the maximum load-bearing capacity was realized for the mix with 10% glass and 0% Phragmites australis fibers. However, the highest ductility index and deflection were achieved for the mix with 10% glass and 0.5% Phragmites australis fibers. Therefore, the use of Phragmites australis fibers can improve the structural performance of concrete.
A Novel MPPT Controller Based on Mud Ring Optimization Algorithm for Centralized Thermoelectric Generator under Dynamic Thermal Gradients
Authors: Zafar Muhammad Hamza , Abou Houran Mohamad , Mansoor Majad , Khan Noman Mujeeb , Moosavi Syed Kumayl Raza , Khan Muhammad Kamran , Akhtar Naureen
Published: March 2023

Most industrial processes generate raw heat. To enhance the efficiency of industrial operations, this raw heat is recovered. Thermoelectric generators (TEG), as solid state devices, provide an excellent application of heat recovery in the form of most manageable electrical power. This work presents a novel MPPT controller based on the Mud Ring Optimization algorithm for a centralized Thermoelectric Generator (TEG) under dynamic thermal gradients. The existing stochastic optimization algorithm for Maximum Power Point Tracking (MPPT) control in renewable energy systems exhibits several limitations that affect its performance in MPPT control. The convergence speed, local minima trap, hyper parameters’ sensitivity toward the population size, acceleration coefficients, and the stopping criterion all impact the convergence stability. In addition to these limitations, sensor noise sensitivity in measurement fluctuates the control system leading to reduced performance. Therefore, the careful design and implementation of the MRO algorithm is crucial to overcome these limitations and achieve a satisfactory performance in MPPT control. The results of this study contribute to developing more efficient MPPT control of TEG systems and implementing renewable energy technologies. The algorithm effectively tracks the maximum power point in dynamic thermal environments and increases the power output compared to conventional MPPT methods. The findings illustrate the efficacy of the proposed controller providing a higher power output (Avg. 99.95%) and faster response time (220 ms) under dynamic thermal conditions achieving 38–70% faster tracking of the GM in dynamic operating conditions.
Vectorized Representation of Commodities by Fusing Multisource Heterogeneous User-Generated Content with Multiple Models
Authors: Man Guangyi , Sun Xiaoyan , Wu Weidong
Published: March 2023

In the field of personalized recommendation, user-generated content (UGC) such as videos, images, and product comments are becoming increasingly important, since they implicitly represent the preferences of users. The vectorized representation of a commodity with multisource and heterogeneous UGC is the key for sufficiently mining the preference information to make a recommendation. Existing studies have mostly focused on using one type of UGC, e.g., images, to enrich the representation of a commodity, ignoring other contents. When more UGC are fused, complicated models with heavy computation cost are often designed. Motivated by this, we proposed a low-computational-power model for vectorizing multisource and recommendation UGC to achieve accurate commodity representations. In our method, video description keyframes, commodities’ attribute text, and user comments were selected as the model’s input. A multi-model fusion framework including feature extraction, vectorization, fusion, and classification based on MobileNet and multilayer perceptrons was developed. In this UGC fusion framework, feature correlations between images and product comments were extracted to design the loss function to improve the precision of vectorized representation. The proposed algorithm was applied to an actual representation of a commodity described by UGC, and the effectiveness of the proposed algorithm was demonstrated by the classification accuracy of the commodity represented.
Physical Modeling and Intelligent Prediction for Instability of High Backfill Slope Moisturized under the Influence of Rainfall Disasters
Authors: Zhang Zhen , Qin Liangkai , Ye Guanbao , Wang Wei , Zhang Jiafeng
Published: March 2023

The stability of high backfill slopes emerges in practice due to the expansion of transportation infrastructures. The seepage and infiltration of rainfall into the backfills brings challenges to engineers in predicting the stability of the slope, weakening the shear strength and modulus of the soil. This study carried out a series of model tests under a plane strain condition to investigate the stability of a high backfill slope moisturized by rainfalls, considering the influences of rainfall duration and intensity. The slope displacements were monitored by a laser displacement sensor and the moisture content in the backfill mass were obtained by a soil moisture sensor. The test results show that increasing the rainfall intensity and duration caused the slope near the surface to be saturated, resulting in significant influences on the lateral displacement of the slope and the reduction of stability as well as the sizes of the sliding mass. Based on the model tests, the numerical analysis was adopted to extend the analysis cases, and the backpropagation (BP) neural network model was further adopted to build a model for predicting the stability of a high backfill slope under rainfall. The trained BP model shows the average relative error of 1.02% and the goodness of fitness of 0.999, indicating a good prediction effect.
Machine Learning Based Representative Spatio-Temporal Event Documents Classification
Authors: Kim Byoungwook , Yang Yeongwook , Park Ji Su , Jang Hong-Jun
Published: March 2023

As the scale of online news and social media expands, attempts to analyze the latest social issues and consumer trends are increasing. Research on detecting spatio-temporal event sentences in text data is being actively conducted. However, a document contains important spatio-temporal events necessary for event analysis, as well as non-critical events for event analysis. It is important to increase the accuracy of event analysis by extracting only the key events necessary for event analysis from among a large number of events. In this study, we define important 'representative spatio-temporal event documents' for the core subject of documents and propose a BiLSTM-based document classification model to classify representative spatio-temporal event documents. We build 10,000 gold-standard training datasets to train the proposed BiLSTM model. The experimental results show that our BiLSTM model improves the F1 score by 2.6% and the accuracy by 4.5% compared to the baseline CNN model.
Multi-Scale Channel Adaptive Time-Delay Neural Network and Balanced Fine-Tuning for Arabic Dialect Identification
Authors: Luo Qibao , Zhou Ruohua
Published: March 2023

The time-delay neural network (TDNN) can consider multiple frames of information simultaneously, making it particularly suitable for dialect identification. However, previous TDNN architectures have focused on only one aspect of either the temporal or channel information, lacking a unified optimization for both domains. We believe that extracting appropriate contextual information and enhancing channels are critical for dialect identification. Therefore, in this paper, we propose a novel approach that uses the ECAPA-TDNN from the speaker recognition domain as the backbone network and introduce a new multi-scale channel adaptive module (MSCA-Res2Block) to construct a multi-scale channel adaptive time-delay neural network (MSCA-TDNN). The MSCA-Res2Block is capable of extracting multi-scale features, thus further enlarging the receptive field of convolutional operations. We evaluated our proposed method on the ADI17 Arabic dialect dataset and employed a balanced fine-tuning strategy to address the issue of imbalanced dialect datasets, as well as Z-Score normalization to eliminate score distribution differences among different dialects. After experimental validation, our system achieved an average cost performance (Cavg) of 4.19% and a 94.28% accuracy rate. Compared to ECAPA-TDNN, our model showed a 22% relative improvement in Cavg. Furthermore, our model outperformed the state-of-the-art single-network model reported in the ADI17 competition. In comparison to the best-performing multi-network model hybrid system in the competition, our Cavg also exhibited an advantage.
A Preliminary Anti-Glare System for Traffic Vehicles Using Polarizing Filters and a Polarizing Flip Plate
Authors: Nguyen Nghia Phan Trong , Phan Minh Ngoc , To Duc Anh , Bui Thang Hung
Published: March 2023

In the past, polarizing filters were attached to cars’ halogen headlights to reduce glare for other vehicles. However, the filters absorbed a significant amount of light and made it difficult for drivers to see properly. Coupled with overheating issues and numerous technical and logistical limitations, polarized automotive lighting systems have not become widespread. In this research, we propose using a polarized LED lighting system to improve drivers’ visibility. Our results demonstrated an illuminance reduction of up to 97.5% when simultaneously using a polarized headlight filter and flip plate. Additionally, our system’s lower operating temperatures resulted in a lifespan increase of approximately 120 times compared to a conventional halogen lighting system.
Analysis and Design of Lateral Framing Systems for Multi-Story Steel Buildings
Authors: Al Dughaishi Husam , Al Lawati Jawad , Alosta Moad , Mahmood Shaker , Al-Kazee Mohamed Faisal , Yusoff Nur Izzi Md , Milad Abdalrhman
Published: March 2023

This study focused on identifying the most appropriate structural system for multi-story buildings and analyzing its response to lateral loads. The study analyzed and compared the different structural systems to determine the most suitable option. The study aims to utilize three lateral framing systems (moment, braced, and diagrid) in order to investigate which system needs the least amount of steel to meet the design requirements. Thus, in order to determine the estimated steel savings of this system as compared to the moment and braced frames, the four-story and eight-story buildings that are 96′ × 96′ in the plane and utilize moment frames, braced frame, and diagrid framing structural systems are presented. Based on the American Society of Civil Engineers (ASCE) 7–10, load combinations are considered for the designs, and the RAM structural analysis is used for the modeling and analysis of the structural systems. The findings of this study’s illustrations were the optimum for the analysis of wind of 176 kips and seismic loads of 122 kips, the building’s lateral displacements, which were the lowest at 0.045 inches, the story drift, the story stiffness, and the story shear for each structural system. In addition, the diagrid system also had the least amount of shear for all the stories, suggesting that it is better able to manage the lateral forces. These results indicate that the diagrid system is a more efficient structural system and can be recommended for use in multi-story buildings.
IoT-Aware Architecture to Guarantee Safety of Maintenance Operators in Industrial Plants
Authors: Montanaro Teodoro , Sergi Ilaria , Stefanizzi Ilaria , Landi Luca , Di Donato Luciano , Patrono Luigi
Published: March 2023

One of the most important factors that influence people’s daily lives and their well-being at work is the so-called “worker safety”. Different literature works demonstrated the positive effects on worker mood and well-being brought by the awareness of being in a safe environment and, consequently, less prone to accidents. Every working environment should guarantee safety protection to employees and operators both in normal operations and extraordinary duties (e.g., maintenance operations), however, the industrial domain is the one that is more exposed to risks for workers. Different technologies already accomplished such requirements in “normal” operations, nonetheless, the literature still lacks solutions to also monitor and guide operators during exceptional and dangerous operations (e.g., maintenance). The combination of IoT and Industry 4.0 can guide the research toward the resolution of the maintenance-related exposed problems. This paper proposes an IoT-aware architecture for the industrial domain to support maintenance operators. It was designed to guide them step by step while real-time monitoring plant, machinery, and other employees working in the same area. During the maintenance procedure, the operator is guided in the proper execution of every single step required by maintenance and an autonomous IoT system monitors the status of the different parts of the plants and machinery to, then, authorize and show, the next steps foreseen in the maintenance process. To test the feasibility and usefulness of the proposed system, a prototype was developed and functionally tested through the exploitation of a machinery simulator and a real lathe machine.
Wavenumber-Frequency Spectra of Normal Mode Function Decomposed Atmospheric Data: Departures from the Dry Linear Theory
Authors: Teruya Andre S. W. , Raphaldini Breno , Mayta Victor C. , Raupp Carlos F. M. , da Silva Dias Pedro L.
Published: March 2023

The study of tropical tropospheric disturbances has led to important challenges from both observational and theoretical points of view. In particular, the observed wavenumber-frequency spectrum of tropical oscillations has helped bridge the gap between observations and the linear theory of equatorial waves. In this study, we obtained a similar wavenumber-frequency spectrum for each equatorial wave type by performing a normal mode function (NMF) decomposition of global Era–Interim reanalysis data. The NMF basis used here is provided by the eigensolutions of the primitive equations in spherical coordinates as linearized around a resting background state. In this methodology, the global multi-level horizontal velocity and geopotential height fields are projected onto the normal mode functions, characterized by a vertical mode, a zonal wavenumber, a meridional quantum index, and a mode type, namely, Rossby, Kelvin, mixed Rossby-gravity, and westward/eastward propagating inertio-gravity modes. The horizontal velocity and geopotential height fields associated with each mode type are then reconstructed in the physical space, as well as their corresponding filtered versions defined according to the vertical mode classes that exhibit barotropic and baroclinic structures within the troposphere. The results reveal expected structures, such as the dominant global-scale Rossby and Kelvin waves constituting the intraseasonal frequency associated with the Madden–Julian Oscillation. On the other hand, a number of unexpected features, such as eastward propagating westward inertio-gravity waves, are revealed by our observed 200 hPa zonal wind spectrum. Among all possible nonlinear processes, we focus on the analysis of the interaction between Kelvin and westward inertio-gravity waves, providing evidence for their coupling. Apart from the nonlinearity, we discuss the potential roles of a vertically/meridionally varying background state as well as the coupling with moist convection in explaining the departures of the observed spectra from the corresponding linear equatorial wave theory.