bluuebunny/crossref_metadata_2025 huggingface dataset:
Segmentation of Individual Leaves of Field Grown Sugar Beet Plant Based on 3D Point Cloud
Authors: Liu Yunling , Zhang Guoli , Shao Ke , Xiao Shunfu , Wang Qing , Zhu Jinyu , Wang Ruili , Meng Lei , Ma Yuntao
Published: April 2022

Accurate segmentation of individual leaves of sugar beet plants is of great significance for obtaining the leaf-related phenotypic data. This paper developed a method to segment the point clouds of sugar beet plants to obtain high-quality segmentation results of individual leaves. Firstly, we used the SFM algorithm to reconstruct the 3D point clouds from multi-view 2D images and obtained the sugar beet plant point clouds after preprocessing. We then segmented them using the multiscale tensor voting method (MSTVM)-based region-growing algorithm, resulting in independent leaves and overlapping leaves. Finally, we used the surface boundary filter (SBF) method to segment overlapping leaves and obtained all leaves of the whole plant. Segmentation results of plants with different complexities of leaf arrangement were evaluated using the manually segmented leaf point clouds as benchmarks. Our results suggested that the proposed method can effectively segment the 3D point cloud of individual leaves for field grown sugar beet plants. The leaf length and leaf area of the segmented leaf point clouds were calculated and compared with observations. The calculated leaf length and leaf area were highly correlated with the observations with R2 (0.80–0.82). It was concluded that the MSTVM-based region-growing algorithm combined with SBF can be used as a basic segmentation step for high-throughput plant phenotypic data extraction of field sugar beet plants.
Machine Learning Strategy for Improved Prediction of Micronutrient Concentrations in Soils of Taif Rose Farms Based on EDXRF Spectra
Authors: Abdelmigid Hala M. , Baz Mohammed A. , AlZain Mohammed A. , Al-Amri Jehad F. , Zaini Hatim Ghazi , Morsi Maissa M. , Abualnaja Matokah , Althagafi Elham A.
Published: April 2022

This study attempts to utilize newly developed machine learning techniques in order to develop a general prediction algorithm for agricultural soils in Saudi Arabia, specifically in the Taif region. Energy dispersive X-ray fluorescence (EDXRF) measurements were used to develop national predictive models that predict the concentrations of 14 micronutrients in soils of Taif rose farms, for providing high-quality data comparable to conventional methods. Machine learning algorithms used in this study included the simple linear model, the multivariate linear regression (MLR); and two nonlinear models, the random forest (RF) and multivariate adaptive regression splines (MARS). Our study proposes a machine learning (ML) strategy for predicting fertility parameters more accurately in agricultural soils using 10 farms of the Taif rose (Rosa damascena) in Taif, Saudi Arabia as a case study. Results demonstrated that MARS provides higher prediction performance when the number of explanatory variables is small, while RF is superior when the number of variables is large. On the other hand, the MLR is recommended as a moderate method for predicting multivariate variables. The study showed that multivariate models can be used to overwhelm the drawbacks of the EDXRF device, such as high detection limits and an element that cannot be directly measured.
The Behavioural Impact on Cats during a Transition from a Clay-Based Litter to a Plant-Based Litter
Authors: Frayne Jennifer , Edwards Michelle , Templeman James R. , Croney Candace C. , MacDonald-Murray Sarah , Flickinger Elizabeth , Verbrugghe Adronie , Shoveller Anna K.
Published: April 2022

Current guidelines recommend transitioning cats from one litter product to another over 6 days to minimize stress. The study objective was therefore to test these guidelines using 16 adult domestic cats (2 cohorts of 8) by observing behavioural changes associated with elimination throughout the litter transition. Cats were transitioned from a clay-based litter (CLAY) to a plant-based litter product (PLANT) over 6 days (period 1) via an incremental replacement of CLAY with PLANT. All cats then remained on PLANT for 8 days (period 2). This same transition process was executed for both cohorts, and litter box behaviours were observed via remote recording. Urination, defecation, cover, and dig behaviours were not different between periods 1 and 2 (p > 0.05). Sniffing frequency was greater in period 2 than period 1 (p < 0.05); however, during the litter transition (period 1), cats sniffed the litter boxes being transitioned from CLAY to PLANT more often and for longer than they did for the boxes consisting of only PLANT (p < 0.05). These data suggest that 6 days may be an adequate amount of time to transition a cat to a new litter, although successful transition may also be specific to the types of litters investigated.
Enteric Methane Emissions and Animal Performance in Dairy and Beef Cattle Production: Strategies, Opportunities, and Impact of Reducing Emissions
Authors: Min Byeng-Ryel , Lee Seul , Jung Hyunjung , Miller Daniel N. , Chen Rui
Published: April 2022

Enteric methane (CH4) emissions produced by microbial fermentation in the rumen resulting in the emission of greenhouse gases (GHG) into the atmosphere. The GHG emissions reduction from the livestock industry can be attained by increasing production efficiency and improving feed efficiency, by lowering the emission intensity of production, or by combining the two. In this work, information was compiled from peer-reviewed studies to analyze CH4 emissions calculated per unit of milk production, energy-corrected milk (ECM), average daily gain (ADG), dry matter intake (DMI), and gross energy intake (GEI), and related emissions to rumen fermentation profiles (volatile fatty acids [VFA], hydrogen [H2]) and microflora activities in the rumen of beef and dairy cattle. For dairy cattle, there was a positive correlation (p < 0.001) between CH4 emissions and DMI (R2 = 0.44), milk production (R2 = 0.37; p < 0.001), ECM (R2 = 0.46), GEI (R2 = 0.50), and acetate/propionate (A/P) ratio (R2 = 0.45). For beef cattle, CH4 emissions were positively correlated (p < 0.05–0.001) with DMI (R2 = 0.37) and GEI (R2 = 0.74). Additionally, the ADG (R2 = 0.19; p < 0.01) and A/P ratio (R2 = 0.15; p < 0.05) were significantly associated with CH4 emission in beef steers. This information may lead to cost-effective methods to reduce enteric CH4 production from cattle. We conclude that enteric CH4 emissions per unit of ECM, GEI, and ADG, as well as rumen fermentation profiles, show great potential for estimating enteric CH4 emissions.
The Relationship between Carcass Condemnations and Tail Lesion in Swine Considering Different Production Systems and Tail Lengths
Authors: Gomes Alice , Romeo Claudia , Ghidini Sergio , Vieira-Pinto Madalena
Published: April 2022

Tail biting has been recognised as an intractable problem in pig production. This study aims to evaluate tail lesion occurrence in slaughtered pigs and explore the relationship between carcass condemnations and tail lesion considering different production systems and tail lengths and to evaluate the importance of creating a detailed tail score classification that includes scarred lesions. Data on a total of 9189 pigs from 73 batches with different tail lengths (undocked; docked mid-length; fully docked) and from distinct production systems (conventional; conventional antibiotic-free and organic) were collected at a Spanish abattoir. Batches with higher tail lesion scores presented a significantly higher chance of total condemnation and total condemnation due to pyaemia, being even more associated with scarring score. The within-batches probability for local condemnations and local condemnation due to abscesses increased significantly with higher scarring scores. Regarding tail length, docked at mid-length and undocked carcasses presented significantly higher odds to be condemned due to abscess. Organic farms showed a higher probability of total condemnations. This research highlights the importance of tail lesions on carcass condemnations that may also be influenced by docking and type of production. Results suggest that scarring score should be included in the tail surveillance program.
The Effects of Water Level Fluctuation on Zooplankton Communities in Shahu Lake Based on DNA Metabarcoding and Morphological Methods
Authors: Qiu Xuemei , Lu Quanfeng , Jia Chenchen , Dai Yuting , Ouyang Shan , Wu Xiaoping
Published: April 2022

Background: The water level of Poyang Lake (China) fluctuates seasonally. Shahu Lake, a smaller body of water connected to Poyang Lake during the wet season, is separated in the dry season. Due to a special fishing method termed ‘lake enclosed in autumn’, the water level is lowered and reaches its lowest point in January, which is <0.5 m deep in the middle of the lake. Our research investigated the effect of water level changes on the zooplankton community composition in Shahu Lake. Methods: We used both DNA metabarcoding method (MBC) (18S rRNA gene V4 region) and morphological method (MOI) to track the zooplankton community structure over four seasons in Shahu Lake (China). Results: Totals of 90 and 98 species of zooplankton were detected by MOI and MBC, respectively, with rotifers being the main zooplankton component. The α-diversity index of both methods increased from spring to summer and decreased from summer to autumn, reaching the lowest value in winter. NMDS and a cluster analysis showed that all zooplankton communities detected by MOI and MBC were significantly separated by season. The zooplankton community in winter was separated from that of the other three seasons, but the summer and autumn communities were more similar. Conclusions: Changes in the water level had significant effects on the zooplankton community composition. We found that MBC was more able to detect the differences in the zooplankton composition than MOI. MBC also had more advantages in copepod recognition. In our study, 37 species of copepods were detected by MBC, but only 11 species were detected by MOI. We concluded that MBC should be used to research the seasonal variations of zooplankton.
Long-Chain Polyunsaturated Fatty Acids n−3 (n−3 LC-PUFA) as Phospholipids or Triglycerides Influence on Epinephelus marginatus Juvenile Fatty Acid Profile and Liver Morphophysiology
Authors: de Mello Paulo H. , Araujo Bruno C. , Marques Victor H. , Branco Giovana S. , Honji Renato M. , Moreira Renata G. , Rombenso Artur N. , Portella Maria C.
Published: April 2022

Phospholipids (PL) are membrane components composed of fatty acids (FA), while triglycerides (TG) are a main source of energy and essential FA. Polyunsaturated FA (PUFA), such as docosahexaenoic acid (DHA), and eicosapentaenoic acid (EPA), are essential for marine carnivorous fish; thus, an 8-week experiment was performed to evaluate the influence of DHA and EPA, provided as PL and TG, on the morphophysiology of Epinephelus marginatus juveniles. A basal diet was manufactured, and DHA and EPA in PL form (PL1—low amount PL2—high amount) and TG form (TG1—low amount; TG2—high amount) were added. Dusky grouper juveniles were equally distributed in 12 tanks of 20 animals each, and liver and muscle were sampled for metabolic analysis. The total hepatic lipids in PL1 and PL2 were higher when compared to the initial, TG1 and TG2 groups. Total lipids in muscle were higher in PL2 and TG1 than PL1 and TG2, respectively. Diets rich in DHA and EPA in PL and TG resulted in higher deposition of these FA in the muscle polar fraction. However, fish fed diets containing lower amounts of DHA and EPA in PL and TG stored those in the muscle neutral fraction and liver, centralizing the storage of DHA and EPA.
Morphology of Starch Particles along the Passage through the Gastrointestinal Tract in Laboratory Mice Fed Extruded and Pelleted Diets
Authors: Wenderlein Jasmin , Kienzle Ellen , Straubinger Reinhard K. , Schöl Heidrun , Ulrich Sebastian , Böswald Linda Franziska
Published: April 2022

Diet processing impacts on starch properties, such as the degree of starch gelatinization. This affects digestibility, as shown in laboratory mice fed either a pelleted or an extruded diet. In the present study, the morphology of starch particles throughout the digestive tract of mice was visualized. Thirty-two female C57BL/6J mice were used for a feeding trial. They were fed a commercial maintenance diet for laboratory mice, which was available in pelleted and extruded form, for seven weeks. The mice were sacrificed after the feeding period, and chyme samples were collected from five sites (stomach, anterior and posterior small intestine, caecum, colon). Samples of diets, chyme and faeces were analyzed via stereomicroscopy (stained with Lugol’s iodine) and scanning electron microscopy (SEM). The starch granules appeared more compact in the pelleted diet, showing first signs of degradation only in the small intestine. The caecum content of both diets group was intensively stained, particles as well as fluid phase, indicating that it contained mainly starch. The SEM pictures of caecum content showed abundant bacteria near starch particles. This suggests selective retention of prae-caecally undigested starch in the murine caecum, likely the site of microbial fermentation.
The High Testosterone Concentrations of the Bucks Used in the “Male Effect” Is Not a Prerequisite for Obtaining High Ovarian Activity in Goats from Mediterranean Latitudes
Authors: Zarazaga Luis Ángel , Gatica María-Carolina , De La Rosa Ignacio , Delgado-Pertíñez Manuel , Guzmán José Luis
Published: April 2022

Two experiments were carried out. Firstly, 54 anestrous females were placed in contact with photostimulated males (Photo; n = 27) or with no photostimulated males (Natural; n = 27). Moreover, a group of bucks treated with artificial photoperiod and a group of bucks subjected to natural photoperiod without contact with females was used (Photo Isolated and Natural Isolated, respectively). In the Natural groups, the testosterone concentrations were similar except for three days after the introduction of the bucks to the does (19.72 ± 4.11 vs. 2.05 ± 0.25 ng/mL for Natural and Natural isolated bucks, respectively, p < 0.05). However, no differences were observed in the Photo groups during the entire experiment. The percentage of females showing estrous was higher in the group of females in contact with photostimulated bucks (96 vs. 74%, respectively, p < 0.05). In the second experiment, a GnRH agonist, deslorelin, was used to regulate the testosterone concentrations of the bucks. Seventy anestrous females were divided into five groups depending on the treatment received by the bucks to which they were exposed: photostimulated bucks (Photo group, n = 14); photostimulated bucks but treated with the agonist at the onset of the photoperiod treatment (Photo-Ago Long group, n = 13); photostimulated bucks but treated with the agonist at the end of the photoperiod treatment (Photo-Ago Short group, n = 15); bucks receiving no photostimulation but treated with the agonist at the end of the photoperiod treatment period (Natural-Ago Short group, n = 13) and bucks receiving no photostimulation nor agonist (Natural group, n = 15). The agonist treatment increased testosterone concentrations after the injection, which remained high for the entire experiment (p < 0.05). Six days after the introduction of the bucks to the does, the testosterone concentrations increased only in the Natural group reaching similar concentrations to the other groups (12.17 ± 6.55, 16.69 ± 4.53, 8.70 ± 0.61, 11.03 ± 1.45 and 14.42 ± 3.64 ng/mL for Photo, Photo-Ago Long, Photo-Ago Short, Natural-Ago Short and Natural bucks, respectively, p > 0.05). No differences in reproductive parameters were observed (p > 0.05). These results demonstrate that, at Mediterranean latitudes, anestrous females can stimulate the testosterone concentrations of bucks after a period of isolation. The high testosterone concentrations are not a prerequisite for an adequate response to the male effect.
Associations of Protein Molecular Structures with Their Nutrient Supply and Biodegradation Characteristics in Different Byproducts of Seed-Used Pumpkin
Authors: Li Yang , Wu Qinghua , Lv Jingyi , Jia Xiaoman , Gao Jianxu , Zhang Yonggen , Wang Liang
Published: April 2022

The purpose of this experiment was to explore the relationship of protein functional groups (including amide I, amide II, α-helix, and β-sheet) in byproducts of seed-used pumpkin (pumpkin seed cake, pumpkin seed coat, and seed-used pumpkin flesh) with their nutrient profiles and biodegradation characteristics. The experiment was designed to use conventional chemical analysis, combining the Cornell Net Carbohydrate and Protein System (CNCPS) and nylon bag technology to assess the nutritional value and biodegradation characteristics of seed-used pumpkin byproducts. Fourier transform infrared spectroscopy (FTIR) was used to analyze the protein molecular structure properties of byproducts of seed-used pumpkin. In this study, we also applied correlation and regression analysis. The results showed that different byproducts of seed-used pumpkin had different in situ biodegradation, nutrient supplies, and spectral structures in the protein region. Among the byproducts of seed-used pumpkin, acid detergent-insoluble crude protein (ADICP) and neutral detergent-insoluble crude protein (NDICP) contents of the pumpkin seed coat were the highest, resulting in the lowest effective degradabilities (EDs) of dry matter and crude protein. The crude protein (CP) ED values were ranked as follows: pumpkin seed cake > seed-used pumpkin flesh > pumpkin seed coat. Significant differences were observed in the peak areas of amide I and amide II and the corresponding peak heights in the two peak areas in the molecular structure of the protein. The peak areas of amide I and amide II and the corresponding peak heights were at the highest levels for pumpkin seed cake, whereas there was no significant difference between the pumpkin seed coat and seed-used pumpkin flesh. Similarly, the peak heights of α-helices and β-sheets were highest for pumpkin seed cake. Correlation and regression results indicated that amide I and amide II area and height, α-helix and β-sheet heights, and area ratios of amide I: amide II, as well as the height ratios of amide I: amide II, and α-helices: β-sheets effectively estimated nutrient supply and that the height ratio of α-helices: β-sheets was mostly sensitive to biodegradation characteristics in different byproducts of seed-used pumpkin. There were significant differences in CP chemical composition and digestibility of different byproducts of seed-used pumpkin that were strongly related to the changes in protein molecular structures.
Investigating a Curcumin-Loaded PLGA-PEG-PLGA Thermo-Sensitive Hydrogel for the Prevention of Alzheimer’s Disease
Authors: Lin Yi-Wen , Fang Chih-Hsiang , Yang Ching-Yun , Liang Ya-Jyun , Lin Feng-Huei
Published: April 2022

In Alzheimer’s disease (AD), the most common cause of dementia, patients generally forget to take pills or skip medication due to side effects, affecting the treatment efficacy. In this study, we combined a poly(lactic-co-glycolic acid), (PLGA)-poly(ethylene glycol), and (PEG)-PLGA thermo-sensitive hydrogel with curcumin (PGC) to deliver an intramuscular injection that could continuously release curcumin and maintain it at a constant level in blood to prevent AD development or progression. We evaluated the drug release profile and cytotoxicity of PGC and its effects on AD pathology through in vitro and in vivo studies and on cognitive function through an aluminum-chloride-induced AD rat model. In the in vitro study, PGC exhibited a lack of cytotoxicity, excellent anti-inflammatory and antioxidant properties, and microglial modulation. In the Morris water maze test, the PGC injection-administered AD rats presented well-focused searching behavior with the shortest swimming path and longest retention times in the quadrant where the platform was initially located. Furthermore, PGC reduced amyloid-beta aggregation and deposition and significantly increased hippocampal activity. This study demonstrated that intramuscular PGC injection can effectively prevent AD development or progression in rats without inducing toxicity; therefore, this strategy could help overcome the present challenges in AD management in humans.
Sp1 S-Sulfhydration Induced by Hydrogen Sulfide Inhibits Inflammation via HDAC6/MyD88/NF-κB Signaling Pathway in Adjuvant-Induced Arthritis
Authors: Li Meng , Hu Wei , Wang Ran , Li Zhaoyi , Yu Yue , Zhuo Yue , Zhang Yida , Wang Zhou , Qiu Yuanye , Chen Keyuan , Ding Qian , Qi Wei , Zhu Menglin , Zhu Yizhun
Published: April 2022

Histone deacetylase 6 (HDAC6) acts as a regulator of the nuclear factor kappa-B (NF-κB) signaling pathway by deacetylating the non-histone protein myeloid differentiation primary response 88 (MyD88) at lysine residues, which is an adapter protein for the Toll-like receptor (TLR) and interleukin (IL)-1β receptor. Over-activated immune responses, induced by infiltrated immune cells, excessively trigger the NF-κB signaling pathway in other effector cells and contribute to the development of rheumatoid arthritis (RA). It has also been reported that HDAC6 can promote the activation of the NF-κB signaling pathway. In the present study, we showed that HDAC6 protein level was increased in the synovium tissues of adjuvant-induced arthritis rats. In addition, hydrogen sulfide (H2S) donor S-propargyl-cysteine (SPRC) can inhibit HDAC6 expression and alleviate inflammatory response in vivo. In vitro study revealed that HDAC6 overexpression activated the NF-κB signaling pathway by deacetylating MyD88. Meanwhile, sodium hydrosulfide (NaHS) or HDAC6 inhibitor tubastatin A (tubA) suppressed the pro-inflammatory function of HDAC6. Furthermore, the reduced expression of HDAC6 appeared to result from transcriptional inhibition by S-sulfhydrating specificity protein 1 (Sp1), which is a transcription factor of HDAC6. Our results demonstrate that Sp1 can regulate HDAC6 expression, and S-sulfhydration of Sp1 by antioxidant molecular H2S ameliorates RA progression via the HDAC6/MyD88/NF-κB signaling pathway.
High Density RF-DC Plasma Nitriding under Optimized Conditions by Plasma-Diagnosis
Authors: Aizawa Tatsuhiko , Rsadi Imron , Yunata Ersyzario Edo
Published: April 2022

This paper is concerned with plasma diagnosis on a N2-H2 gas mixture to determine the optimum parameters for the nitriding process. Plasma parameters such as pressure, RF-voltage, and DC-bias were varied for optimization. The active species such as N2+ and NH were identified in plasma diagnosis. In the N2-H2 gas mixture, hydrogen imposed a great influence on plasma generation. The small addition of a hydrogen molecule into the gas mixture resulted in the highest yield of N2+ ions and NH radicals; the optimum hydrogen content was 20% in the mixture. The austenitic stainless-steel type AISI304 was nitrided at 673 K and 623 K to experimentally demonstrate that hydrogen gas content optimization is necessary to improve the surface hardness and to describe low temperature nitriding under high nitrogen flux at the surface.
A Deep Learning Approach for Sentiment Analysis of COVID-19 Reviews
Authors: Singh Chetanpal , Imam Tasadduq , Wibowo Santoso , Grandhi Srimannarayana
Published: April 2022

User-generated multi-media content, such as images, text, videos, and speech, has recently become more popular on social media sites as a means for people to share their ideas and opinions. One of the most popular social media sites for providing public sentiment towards events that occurred during the COVID-19 period is Twitter. This is because Twitter posts are short and constantly being generated. This paper presents a deep learning approach for sentiment analysis of Twitter data related to COVID-19 reviews. The proposed algorithm is based on an LSTM-RNN-based network and enhanced featured weighting by attention layers. This algorithm uses an enhanced feature transformation framework via the attention mechanism. A total of four class labels (sad, joy, fear, and anger) from publicly available Twitter data posted in the Kaggle database were used in this study. Based on the use of attention layers with the existing LSTM-RNN approach, the proposed deep learning approach significantly improved the performance metrics, with an increase of 20% in accuracy and 10% to 12% in precision but only 12–13% in recall as compared with the current approaches. Out of a total of 179,108 COVID-19-related tweets, tweets with positive, neutral, and negative sentiments were found to account for 45%, 30%, and 25%, respectively. This shows that the proposed deep learning approach is efficient and practical and can be easily implemented for sentiment classification of COVID-19 reviews.
Recent Development of High-Energy Short-Pulse Lasers with Cryogenically Cooled Yb:YAG
Authors: Sui Yuan , Yuan Mingheng , Bai Zhenao , Fan Zhongwei
Published: April 2022

High-power solid-state lasers are among the hot research directions at the forefront of laser research and have major applications in industrial processing, laser-confined nuclear fusion, and high-energy particle sources. In this paper, the properties of Yb:YAG and Nd:YAG crystals as gain media for high-power solid-state lasers were briefly compared, according to the results of which Yb:YAG crystals are more suitable for high-power applications. Then, the effects of the thermodynamic and spectral properties of Yb:YAG crystals with temperature were analyzed in detail, and it was shown that the laser beams amplified by the cryogenically cooled Yb:YAG crystals could have higher beam quality, higher pump absorption efficiency, lower pump threshold, and higher gain. The change in properties of Yb:YAG crystal at low temperature makes it more suitable as a gain medium for high-power lasers. Subsequently, two types of kilowatt-class lasers using cryogenically cooled Yb:YAG crystals as gain media are introduced—100 J, 10 Hz nanosecond lasers and 1 J, 1 kHz picosecond lasers. Their configuration, main parameters, and typical output results were analyzed. Finally, future directions in the development of cryogenically cooled Yb:YAG lasers are discussed.
An On-Chip Silicon Photonics Thermometer with Milli-Kelvin Resolution
Authors: Wang Jin , Pan Yijie , Gao Jianxin , Zhang Cheng , Qu Zhier , Xu Tongtong , Shen Yang , Qu Jifeng
Published: April 2022

Photonic-based thermometers have been attracting intense research interest as a potential alternative to traditional electrical thermometers due to their physical and chemical stability and immunity to electromagnetic interference. However, due to the high requirements for the stability of the laser source, the existing studies on resolution are only theoretical predictions and do not include real-measured results. In this paper, we report on the fabrication and characterization of an on-chip silicon whispering-gallery-mode (WGM) ring resonator thermometer. The strip grating and the ring structure were fabricated on the silicon-on-insulator (SOI) substrate by two-step etching. The quality-factor (Q-factor), temperature sensitivity, and measurement range of the packaged device were 21,400, 42 pm/K, and 150 K, respectively. The real-measured temperature resolution of 2.9 mK was achieved by virtue of the power and polarization stabilization of the laser source.
Analysis of the Motion Sickness and the Lack of Comfort in Car Passengers
Authors: Asua Estibaliz , Gutiérrez-Zaballa Jon , Mata-Carballeira Oscar , Ruiz Jon Ander , del Campo Inés
Published: April 2022

Advanced driving assistance systems (ADAS) are primarily designed to increase driving safety and reduce traffic congestion without paying too much attention to passenger comfort or motion sickness. However, in view of autonomous cars, and taking into account that the lack of comfort and motion sickness increase in passengers, analysis from a comfort perspective is essential in the future car investigation. The aim of this work is to study in detail how passenger’s comfort evaluation parameters vary depending on the driving style, car or road. The database used has been developed by compiling the accelerations suffered by passengers when three drivers cruise two different vehicles on different types of routes. In order to evaluate both comfort and motion sickness, first, the numerical values of the main comfort evaluation variables reported in the literature have been analyzed. Moreover, a complementary statistical analysis of probability density and a power spectral analysis are performed. Finally, quantitative results are compared with passenger qualitative feedback. The results show the high dependence of comfort evaluation variables’ value with the road type. In addition, it has been demonstrated that the driving style and vehicle dynamics amplify or attenuate those values. Additionally, it has been demonstrated that contributions from longitudinal and lateral accelerations have a much greater effect in the lack of comfort than vertical ones. Finally, based on the concrete results obtained, a new experimental campaign is proposed.
Multi-Criteria Decision Making in the PMEDM Process by Using MARCOS, TOPSIS, and MAIRCA Methods
Authors: Nguyen Huu-Quang , Nguyen Van-Tung , Phan Dang-Phong , Tran Quoc-Hoang , Vu Ngoc-Pi
Published: April 2022

Multi-criteria decision making (MCDM) is used to determine the best alternative among various options. It is of great importance as it hugely affects the efficiency of activities in life, management, business, and engineering. This paper presents the results of a multi-criteria decision-making study when using powder-mixed electrical discharge machining (PMEDM) of cylindrically shaped parts in 90CrSi tool steel. In this study, powder concentration, pulse duration, pulse off time, pulse current, and host voltage were selected as the input process parameters. Moreover, the Taguchi method was used for the experimental design. To simultaneously ensure minimum surface roughness (RS) and maximum material-removal speed (MRS) and to implement multi-criteria decision making, MARCOS (Measurement of Alternatives and Ranking according to Compromise Solution), TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution), and MAIRCA (Multi-Attributive Ideal–Real Comparative Analysis) methods were applied. Additionally, the weight calculation for the criteria was calculated using the MEREC (Method based on the Removal Effects of Criteria) method. From the results, the best alternative for the multi-criteria problem with PMEDM cylindrically shaped parts was proposed.
Blockchain Applications in Forestry: A Systematic Literature Review
Authors: He Zhaoyuan , Turner Paul
Published: April 2022

Blockchain applications have received a lot of attention in recent years. They provide enormous benefits and advantages to many different sectors. To date, there have not been any systematic studies comprehensively reviewing current blockchain-based applications in the forestry sector. This paper examines published work on blockchain-based applications in the forestry sector. A systematic review was conducted to identify, analyze, and discuss current literature on current blockchain applications deployed (and/or proposed) in the forestry sector, grouping results into three domains of forest management, traceability of forest-based products, and forest fire detection based on content analysis. The analyses highlight reported benefits, opportunities, and challenges of blockchain applications in the forestry sector. The study results show that blockchain has great potential in sustainable forestry, minimizing illegal logging, conserving biodiversity, and many other areas in forestry. It also shows that blockchain in forestry is still immature and complex, since it requires specialists to adopt. This paper contributes towards filling the existing research gap through this systematic review on blockchain applications in forestry. This review offers insights into a deep understanding of blockchain applications for managers, practitioners, and consultants interested in forestry. The paper identifies existing research gaps on related topics of blockchain applications in forestry and makes recommendations on potential future directions for research into blockchain in forestry.
From Pigments to Pixels: A Comparison of Human and AI Painting
Authors: Sun Yikang , Yang Cheng-Hsiang , Lyu Yanru , Lin Rungtai
Published: April 2022

From entertainment to medicine and engineering, artificial intelligence (AI) is now being used in a wide range of fields, yet the extent to which AI can be effectively applied to the creative arts remains to be seen. In this research, a neural algorithm of artistic style was used to generate six AI paintings and these were compared with six paintings on the same theme by an amateur painter. Two sets of paintings were compared by 380 participants, 70 percent of whom had previous painting experience. Results indicate that color and line are the key elements of aesthetic appreciation. Additionally, the style transfer had a marked effect on the viewer when there was a close correspondence between the painting and the style transfer but not when there was little correspondence, indicating that AI is of limited effectiveness in modifying an existing style. Although the use of neural networks simulating human learning has come a long way in narrowing the gap between paintings produced by AI and those produced in the traditional fashion, there remains a fundamental difference in terms of aesthetic appreciation since paintings generated by AI are based on technology, while those produced by humans are based on emotion.
Diagnosis of Artificial Flaws from Eddy Current Testing Signals Based on Sweep Frequency Non-Destructive Evaluation
Authors: Vaverka Filip , Smetana Milan , Gombarska Daniela , Janousek Ladislav
Published: April 2022

An investigation of artificial flaws in electromagnetic non-destructive evaluation using eddy-current frequency-response analysis is carried out in this study. A new approach incorporating innovative solution is proposed. The goal was to increase the resolution of gained signals in contrast to the conventional sweep-frequency method. The proposed procedure was tested on real material specimens where differential responses were gained from artificial electro-discharge machined flaws. Two plate specimens having EDM flaws of various dimensions were inspected. Eddy-current responses due to the material flaws were sensed and compared to a dataset that was obtained by numerical modelling. The presented unique results clearly show that the resolution of a fixed probe driven with sweep-frequency excitation signal can be increased when the appropriate probe instrumentation is used and the characteristics are further mathematically processed.
A Deep Learning Framework Performance Evaluation to Use YOLO in Nvidia Jetson Platform
Authors: Shin Dong-Jin , Kim Jeong-Joon
Published: April 2022

Deep learning-based object detection technology can efficiently infer results by utilizing graphics processing units (GPU). However, when using general deep learning frameworks in embedded systems and mobile devices, processing functionality is limited. This allows deep learning frameworks such as TensorFlow-Lite (TF-Lite) and TensorRT (TRT) to be optimized for different hardware. Therefore, this paper introduces a performance inference method that fuses the Jetson monitoring tool with TensorFlow and TRT source code on the Nvidia Jetson AGX Xavier platform. In addition, central processing unit (CPU) utilization, GPU utilization, object accuracy, latency, and power consumption of the deep learning framework were compared and analyzed. The model is You Look Only Once Version4 (YOLOv4), and the dataset uses Common Objects in Context (COCO) and PASCAL Visual Object Classes (VOC). We confirmed that using TensorFlow results in high latency. We also confirmed that TensorFlow-TensorRT (TF-TRT) and TRT using Tensor Cores provide the most efficiency. However, it was confirmed that TF-Lite showed the lowest performance because it utilizes a GPU limited to mobile devices. Through this paper, we think that when developing deep learning-related object detection technology on the Nvidia Jetson platform or desktop environment, services and research can be efficiently conducted through measurement results.
Less Rare-Earth Electromagnetic Design for a High-Performance Permanent Magnet Motor
Authors: Rivera Christian A. , Ugalde Gaizka , Poza Javier , Garramiola Fernando , Badiola Xabier
Published: April 2022

This paper presents an electromagnetic design alternative using the so-called banana-shaped magnets, achieving magnet weight reduction of 21.82% for the same performance as the baseline motor in the case study. Typically, parallel magnetization is used in this topology because it provides the manufacturing advantage of not building a specific magnetizing device required to achieve radial magnetization. Therefore, as its main contribution, this paper proposes using tilted magnetization, demonstrating that the performance is better than the conventional way of applying parallel magnetization in banana-shaped motors but still using parallel magnetization. Because of the performance improvement for the same motor structure, magnet weight reduction is possible for a new design with the same performance as the baseline motor. In addition, this paper presents the workflow followed to obtain the less rare-earth design motor candidate using tilted magnetization.
Impact and Challenges of Reducing Petroleum Consumption for Decarbonization
Authors: Matsumoto Ryoma , Tabata Tomohiro
Published: April 2022

This study aimed to identify the impact of achieving the 1.5 °C target on the petroleum supply chain in Japan, and discuss the feasibility and challenges of decarbonization. First, a national material flow was established for the petroleum supply chain in Japan, including processes for crude petroleum refining, petroleum product manufacturing, plastic resin and product manufacturing, and by-product manufacturing. In particular, by-product manufacturing processes, such as hydrogen, gaseous carbon dioxide, and sulfur, were selected because they are utilized in other industries. Next, the outlook for the production of plastic resin, hydrogen, dry ice produced from carbon dioxide gas, and sulfur until 2050 was estimated for reducing petroleum consumption required to achieve the 1.5 °C target. As a result, national petroleum treatment is expected to reduce from 177,048.00 thousand kl in 2019 to 126,643.00 thousand kl in 2030 if the reduction in petroleum consumption is established. Along with this decrease, plastic resin production is expected to decrease from 10,500.00 thousand ton in 2019 to 7511.00 thousand ton by 2030. Conversely, the plastic market is expected to grow steadily, and the estimated plastic resin production in 2030 is expected to be 20,079.00 thousand ton. This result indicates that there is a large output gap between plastic supply and demand. To mitigate this gap, strongly promoting the recycling of waste plastics and making the price competitiveness of biomass plastics equal to that of petroleum-derived plastics are necessary.
Development of Vehicle Emission Model Based on Real-Road Test and Driving Conditions in Tianjin, China
Authors: Zhang Yi , Zhou Ran , Peng Shitao , Mao Hongjun , Yang Zhiwen , Andre Michel , Zhang Xin
Published: April 2022

Based on the demand of vehicle emission research and control, this paper presents the development of a portable vehicle measurement system (PEMS) based on SEMTECH-DS and ELPI+, the vehicle emission tests carried out on actual roads, and the data obtained for the establishment and validation of a vehicle emission model. Based on the results of the vehicle emission test, it was found that vehicle driving conditions (speed, acceleration, vehicle specific power (VSP), etc.) had a significant impact on the pollutant emission rate. In addition, local driving cycles were generated and the frequency distribution of VSP-bin under different cycles was analyzed. Then, through the establishment of an emission rate database, calculation of emission factors and validation of the emission model, a vehicle emission model based on actual road driving conditions was developed by taking VSP as the “surrogate variables”. It showed that the emission factor model established in this study could better reflect the vehicle transient emissions on the actual road with high accuracy and local adaptability. Through this study, it could be found that due to the great differences in traffic development modes and vehicle driving conditions in different cities in China, the emission model based on driving conditions was a better choice to carry out the research on vehicle emission in Chinese cities. Compared with directly applying international models or quoting the recommended values of relevant macroscopic guidelines, the emission factor model established in this study, using actual driving conditions, could better reflect the vehicle transient emissions on the actual road with high accuracy and local adaptability. In addition, due to the rapid development of China’s urban traffic and the rapid change of driving conditions, it was of great significance to regularly update China’s urban conditions to improve the accuracy of the model, no matter which model was chosen.
The Response Mechanism and Threshold of Spring Wheat to Rapid Drought
Authors: Chen Fei , Wang Heling , Zhao Funian , Wang Runyuan , Qi Yue , Zhang Kai , Zhao Hong , Tang Guoying , Yang Yang
Published: April 2022

In order to deeply understand the effect mechanism of rapid drought stress on the physiological and biochemical properties of crop leaves and determine drought thresholds, the potted spring wheat under two water treatments, adequate water supply and continuous drought stress, was researched. In the early stage of drought, the parameters of leaves decreased in the order of stomatal conductance (gs), intercellular CO2 concentration (Ci), maximum electron transfer rate (Jmax), mesophyll conductance (gm), photosynthetic rate (Pn,) leaf water content (LWC), triose phosphate utilization rate (TPU), transpiration rate (Tr), and maximum carboxylation rate (Vcmax). Photosynthesis was dominated by stomatal limitation and also limited by carboxylation and mesophyll limitation. The carboxylation limitation was mainly caused by the reduction of electron transport capacity. In the late stage of drought, stomatal limitation first decreased, and then mesophyll limitation decreased. During extreme drought, carboxylation limitation also decreased. With the decrease of relative soil moisture (RSM), except for Ci, which first decreased and then increased, other physicochemical parameters of leaves all showed an S-shaped, decreasing trend. Mild and severe drought thresholds were determined to be 56.6% and 43.6% of the RSM, respectively, according to the curve’s inflection point, corresponding to 16.6% and about 52.2% of the average initial decrease amplitude among all parameters. This will provide a reference for monitoring as well as an early warning of rapid drought in spring wheat.
Spark Configurations to Optimize Decision Tree Classification on UNSW-NB15
Authors: Bagui Sikha , Walauskis Mary , DeRush Robert , Praviset Huyen , Boucugnani Shaunda
Published: April 2022

This paper looks at the impact of changing Spark’s configuration parameters on machine learning algorithms using a large dataset—the UNSW-NB15 dataset. The environmental conditions that will optimize the classification process are studied. To build smart intrusion detection systems, a deep understanding of the environmental parameters is necessary. Specifically, the focus is on the following environmental parameters: the executor memory, number of executors, number of cores per executor, execution time, as well as the impact on statistical measures. Hence, the objective was to optimize resource usage and minimize processing time for Decision Tree classification, using Spark. This shows whether additional resources will increase performance, lower processing time, and optimize computing resources. The UNSW-NB15 dataset, being a large dataset, provides enough data and complexity to see the changes in computing resource configurations in Spark. Principal Component Analysis was used for preprocessing the dataset. Results indicated that a lack of executors and cores result in wasted resources and long processing time. Excessive resource allocation did not improve processing time. Environmental tuning has a noticeable impact.
Lactide: Production Routes, Properties, and Applications
Authors: Cunha Bruna L. C. , Bahú Juliana O. , Xavier Letícia F. , Crivellin Sara , de Souza Samuel D. A. , Lodi Leandro , Jardini André L. , Filho Rubens Maciel , Schiavon Maria I. R. B. , Concha Viktor O. Cárdenas , Severino Patricia , Souto Eliana B.
Published: April 2022

Lactide dimer is an important monomer produced from lactic acid dehydration, followed by the prepolymer depolymerization process, and subsequent purification. As lactic acid is a chiral molecule, lactide can exist in three isomeric forms: L-, D-, and meso-lactide. Due to its time-consuming synthesis and the need for strict temperature and pressure control, catalyst use, low selectivity, high energy cost, and racemization, the value of a high purity lactide has a high cost in the market; moreover, little is found in scientific articles about the monomer synthesis. Lactide use is mainly for the synthesis of high molar mass poly(lactic acid) (PLA), applied as bio-based material for medical applications (e.g., prostheses and membranes), drug delivery, and hydrogels, or combined with other polymers for applications in packaging. This review elucidates the configurations and conditions of syntheses mapped for lactide production, the main properties of each of the isomeric forms, its industrial production, as well as the main applications in the market.
Polymorphisms in Genes Involved in Inflammation and Periodontitis: A Narrative Review
Authors: Brodzikowska Aniela , Górski Bartłomiej
Published: April 2022

Current evidence pinpoints that the variability in periodontitis traits in humans may be attributable to genetic factors. Different allelic variants can result in alterations in tissue structure, antibody responses and inflammatory mediators. Consequently, genetic variations may act as protective or risk factors for periodontal diseases. A number of features of the inflammatory and immune response that seem to play a role in the development of periodontitis have a clearly established genetic basis. Identifying genes that contribute to the pathogenesis of periodontitis may be utilized for risk assessment in both aggressive and chronic periodontitis. The aim of this narrative review is to summarize the role of polymorphisms in genes involved in inflammation and periodontitis, including cellular receptors, tissue compatibility antigens, antibodies and cytokines.