bluuebunny/crossref_metadata_2025 huggingface dataset:
Genome-Wide Identification and Expression Analysis of Cytosine DNA Methyltransferase Genes Related to Somaclonal Variation in Pineapple (Ananas comosus L.)
Authors: Lin Wenqiu , Xiao Xi’ou , Sun Weisheng , Liu Shenghui , Wu Qingsong , Yao Yanli , Zhang Hongna , Zhang Xiumei
Published: April 2022

DNA methylation plays an important role in somaclonal variation. Cytosine-5 DNA methyltransferases (C5-MTases) are crucial enzymes for maintaining the de novo genome DNA methylation status, and the gene family has been identified and characterized in several species. However, limited information is available about the role of C5-MTases in the somaclonal variation of pineapple. Herein, the characteristic of DNA methylation in the leaf variants of pineapple showed that the methylation rate of variants decreased and the demethylation was mainly. Six AcC5-MTases were identified from pineapple genome. Phylogenetic analysis indicated that the six members could be classified into four subgroups, namely, AcMET, AcCMT, AcDRM, and AcDNMT, demonstrating evolutionary conservation in the C5-MTases across pineapple and other plant species. Cis-elements were presented in AcC5-MTase promoters, including light-responsive, phytohormone-responsive, and plant growth and development elements. Furthermore, we investigated the expression profiles of AcC5-MTases in different tissues and their transcript abundance in the leaves of somaclonal variation. Interestingly, most AcC5-MTase genes were highly expressed in leaf and carpopodium. AcMET, AcCMT2, and AcDRM2 were upregulated in pineapple somaclonal variants, indicating that AcC5-MTases might play an important role in the somaclonal variation of pineapple. Our results will aid in understanding the complex roles of methylation in plants and provide a basis for analyzing the role of methylation modification in the somaclonal variation of pineapple.
Effects of Biostimulants in Horticulture, with Emphasis on Ornamental Plant Production
Authors: Kisvarga Szilvia , Farkas Dóra , Boronkay Gábor , Neményi András , Orlóci László
Published: April 2022

The biostimulant segment is becoming increasingly important worldwide. One of the reasons for this is that fewer plant protection products are placed on the market in the European Union, and environmental sustainability also plays an important role in their use. Biostimulants are often used in several horticultural sectors, including ornamentals, to strengthen plants, achieve commercial standards, produce quality goods, increase plant vitality, and aid harvesting. This paper presents the latest results of the use of biostimulants in horticulture, with special emphasis on ornamental plant production. The legal regulation of biostimulants and their regulatory mechanisms are described in detail in the review. The main groups of biostimulants are also discussed. The response of plants to abiotic stress, in particular physiological, anatomical, and genetic changes, with regard to the application of biostimulants is also detailed. Focus is given to the areas of ornamental crop production, such as sexual and asexual propagation, cultivation, and harvesting, where biostimulants are used.
Surface Soil Moisture Retrieval Using Sentinel-1 SAR Data for Crop Planning in Kosi River Basin of North Bihar
Authors: Parida Bikash Ranjan , Pandey Arvind Chandra , Kumar Randhir , Kumar Sourav
Published: April 2022

Surface Soil Moisture (SSM) is a key factor for understanding the physical process between the land surface and atmosphere. With the advancement of Synthetic Aperture Radar (SAR) technology and backscattering models, retrieval of SSM over the land surface at higher spatial resolution became effective and accurate. This study examines the potential of C-band Sentinel-1 SAR data to derive SSM in a dry season (February 2020) over bare soil and vegetated agricultural fields in the Kosi River Basin (KRB) in North Bihar. Field campaigns were conducted simultaneously with Sentinel–1A acquisition date, and measurements comprised 54 in-situ sampling plots for the top of the soil (0–7.6 cm depth) using time-domain reflectometry (TDR–300). The modified Dubois model was employed to estimate relative soil permittivity from the backscatter values (σ°) of VV polarization. With the help of Topp’s model, volumetric SSM (m3/m3) was derived for all areas with normalized difference vegetation index (NDVI) less than 0.4 that majorly covered bare land or sparse vegetation. The key findings demonstrated that model-derived SSM was well correlated with the in-situ SSM with the coefficient of determination (R2) of 0.77 and root mean square error (RMSE) of 0.06 m3/m3. The spatial distribution of SSM ranged from 0.05 to 0.5 m3/m3 over the KRB, and the highest moisture was found in the Kosi Megafan. The modified Dubois model was effective in providing SSM from Sentinel–1A data in bare soil and agricultural fields and, thus, supporting use in hydrological, meteorological and crop planning applications.
Hot Foam and Nitrogen Application to Promote Spring Transition of “Diamond” Zoysiagrass (Zoysia matrella (L.) Merr.) Overseeded with Perennial Ryegrass (Lolium perenne L.)
Authors: Caturegli Lisa , Sportelli Mino , Pirchio Michel , Sciusco Giuliano , Volterrani Marco , Tucci Matteo , Magni Simone , Minelli Alberto , Fontanelli Marco , Frasconi Christian , Raffaelli Michele , Peruzzi Andrea
Published: April 2022

In transition areas, cool season turfgrasses are overseeded in autumn to maintain the high quality of dormant warm season turfgrasses, while in spring several agronomic methods (scalping, coring, topdressing, verticutting, irrigation, and targeted fertilization) or chemical desiccation are adopted to remove the cool season turfgrasses from the stand. To reduce chemical applications, several methods of “thermal weeding” have been experimented with, but little is known about these methods in zoysiagrass (Zoysia spp. Willd) spring transition. A study was conducted at the University of Pisa, Italy, on Manila grass (Zoysia matrella (L.) Merr., cv “Diamond”) (Zm) overseeded with perennial ryegrass (Lolium perenne L.) (Lp) with the aim of comparing different methods of cool season grass suppression (scalping and hot foam) and different application rates of nitrogen. To assess treatment effect, green cover, turf quality, turf color, shoot density, and some vegetation indices (GLI, DGCI and NDVI) were determined. An average green cover of at least 90% was obtained on all plots seven weeks after the treatments. While scalping had minor effects on turf appearance and on polystand composition, hot foam had a stronger effect on turf color, green cover, and turf quality in the weeks following application. Once it had recovered from the hot foam treatments, the turf had a greater number of Zm shoots and a relevant reduction of Lp shoots. The hot foam was very effective in suppressing Lp while maintaining Zm recovery capacity.
Estimation of Winter Wheat Residue Coverage Based on GF-1 Imagery and Machine Learning Algorithm
Authors: Zhu Qilei , Xu Xingang , Sun Zhendong , Liang Dong , An Xiaofei , Chen Liping , Yang Guijun , Huang Linsheng , Xu Sizhe , Yang Min
Published: April 2022

Crop residue is an important component of farmland ecosystems, which is of great significance for increasing soil organic carbon, mitigating wind erosion and water erosion and conserving soil and water. Crop residue coverage (CRC) is an important parameter to characterize the number and distribution of crop residues, and also a key indicator of conservation tillage. In this study, the CRC of wheat was taken as the research object. Based on the high-resolution GF-1 satellite remote sensing imagery from China, decision tree (DT), gradient boosting decision tree (GBDT), random forest (RF), least absolute shrinkage and selection operator (LASSO), extreme gradient boosting regression (XGBR) and other machine learning algorithms were used to carry out the estimation of wheat CRC by remote sensing. In addition, the comparisons with sentinel-2 imagery data were also utilized to assess the potential of GF satellite data for CRC estimates. The results show the following: (1) Among the spectral indexes using shortwave infrared characteristic bands from sentinel-2 imagery, the dead fuel index (DFI) was the best for estimating wheat CRC, with an R2 of 0.54 and an RMSE of 10.26%. The ratio vegetation index (RVI) extracted from visible and near-infrared characteristic bands from GF-1 data performed the best, with an R2 of 0.46 and an RMSE of 11.39%. The spectral index extracted from GF-1 and sentinel-2 images had a significant response relationship with wheat residue coverage. (2) When only the characteristic bands from the visible and near-infrared spectral ranges were applied, the effects of the spatial resolution differences of different images on wheat CRC had to be taken into account. The estimations of wheat CRC with the high-resolution GF-1 data were significantly better than those with the Sentinel-2 data, and among multiple machine learning algorithms adopted to estimate wheat CRC, LASSO had the most stable capability, with an R2 of 0.46 and an RMSE of 11.4%. This indicates that GF-1 high-resolution satellite imagery without shortwave infrared bands has a good potential in applications of monitoring crop residue coverage for wheat, and the relevant technology and method can also provide a useful reference for CRC estimates of other crops.
Analysis of the Dynamics of Productive Performance of Organic Farming in the European Union
Authors: Ionescu Romeo Victor , Zlati Monica Laura , Antohi Valentin Marian , Fortea Costinela , Petrea Stefan Mihai , Cristea Dragos Sebastian
Published: April 2022

This research is focused on identifying the potential of organic farming by testing the efficiency of productive yields and identifying pragmatic means to quantify it such as the function of the productive yield of organic farming. The results of the study are concretized in the definition of a new tool (the organic productivity function) and its testing in order to capture the evolution of organic farming in relation to external influencing factors (economic and epidemiological crises) during the analyzed period and the influence of support measures adopted at European level. The study is useful to national and supranational decision makers for adjusting organic agriculture development strategies.
Genetic Differentiation among Livestock Breeds—Values for Fst
Authors: Hall Stephen J. G.
Published: April 2022

(1) Background: The Fst statistic is widely used to characterize between-breed relationships. Fst = 0.1 has frequently been taken as indicating genetic distinctiveness between breeds. This study investigates whether this is justified. (2) Methods: A database was created of 35,080 breed pairs and their corresponding Fst values, deduced from microsatellite and SNP studies covering cattle, sheep, goats, pigs, horses, and chickens. Overall, 6560 (19%) of breed pairs were between breeds located in the same country, 7395 (21%) between breeds of different countries within the same region, 20,563 (59%) between breeds located far apart, and 562 (1%) between a breed and the supposed wild ancestor of the species. (3) Results: General values for between-breed Fst were as follows, cattle: microsatellite 0.06–0.12, SNP 0.08–0.15; sheep: microsatellite 0.06–0.10, SNP 0.06–0.17; horses: microsatellite 0.04–0.11, SNP 0.08–0.12; goats: microsatellite 0.04–0.14, SNP 0.08–0.16; pigs: microsatellite 0.06–0.27, SNP 0.15–0.22; chickens: microsatellite 0.05–0.28, SNP 0.08–0.26. (4) Conclusions: (1) Large amounts of Fst data are available for a substantial proportion of the world’s livestock breeds, (2) the value for between-breed Fst of 0.1 is not appropriate owing to its considerable variability, and (3) accumulated Fst data may have value for interdisciplinary research.
Activities of Antioxidant and Proteolytic Systems and Biomarkers in the Fat Body and Hemolymph of Young Apis mellifera Females
Authors: Strachecka Aneta , Kuszewska Karolina , Olszewski Krzysztof , Skowronek Patrycja , Grzybek Maciej , Grabowski Marcin , Paleolog Jerzy , Woyciechowski Michał
Published: April 2022

The proteolytic and antioxidant systems are important components of humoral immunity, and these biomarkers indicate the immune status. These compounds are synthesized in the bees’ fat body and released into the hemolymph. Their functions maintain the organism’s homeostasis and protect it against adverse environmental factors (including pathogens). We determined the activities of acidic, neutral, and alkaline proteases and their inhibitors, as well as superoxide dismutase (SOD), catalase (CAT), aspartate aminotransferase (AST), alanine aminotransferase (ALT), alkaline phosphatase (ALP), and the level of total antioxidant potential (TAC). These compounds were investigated in the fat body and hemolymph in the females with increased reproductive potential, i.e., queens and rebels, and in normal (non-reproductive sterile non-rebel) workers. The phenoloxidase (PO) activities were determined in the hemolymph. The normal workers had higher activities of proteases and their inhibitors, SOD and CAT, in the fat body and hemolymph, compared to the queens and rebels. The protease inhibitors were not usually active in the queens. As we predicted, the rebels revealed values between those of the queens and normal workers. The highest activities of proteases and antioxidants were identified in the fat body from the third tergite in comparison with the sternite and the fifth tergite. These results are important for oxidative stress ecology and give a better understanding of the functioning of the fat body and the division of labor in social insects.
Long Term Dietary Supplementation with Omega-3 Fatty Acids in Charolais Beef Cattle Reared in Italian Intensive Systems: Nutritional Profile and Fatty Acids Composition of Longissimus lumborum Muscle
Authors: Corino Carlo , Vizzarri Francesco , Ratti Sabrina , Pellizzer Mirco , Rossi Raffaella
Published: April 2022

Recently, the quality of beef has received great attention, and health concerns have been focused on fatty acid composition in relation to dietary requirements. The present work aims to evaluate the effect of omega-3 fatty acids (FA) lipid supplement in beef diet on the nutritional characteristics of Longissimus lumborum (LL) muscle. One hundred and eighty Charolais beef were divided in two groups: the control group (CON) received a basal diet and the second one (TR) an isoenergetic diet containing the omega-3 supplement. Dietary treatment did not affect (p > 0.05) growth performances, carcass characteristics and LL colour indices. Cholesterol content resulted lower (p < 0.001) in LL muscle from TR group than CON. The omega-3 FA and conjugated linoleic acid content were higher (p < 0.001) in LL muscle from TR than CON. As expected, LL muscle from TR group showed an increased value of malondialdehyde than CON during refrigerated storage, anyway, remaining within the threshold value of 1 mg/kg meat. In conclusion, the lipid supplement, rich in omega-3 FA improves the fatty acid profile and decreases cholesterol content of LL muscle. This feeding practice is suggested to enhance the nutritional value of meat from beef reared in intensive condition, improving the consumer’s health.
Antimicrobial Dispensing Practice in Community Pharmacies in Russia during the COVID-19 Pandemic
Authors: Rachina Svetlana , Kozlov Roman , Kurkova Anastasiya , Portnyagina Ulyana , Palyutin Shamil , Khokhlov Aleksandr , Reshetko Olga , Zhuravleva Marina , Palagin Ivan ,   on behalf of Russian Working Group of the Project
Published: April 2022

COVID-19 has had a significant impact on health care systems, including drug use. The present study aimed to evaluate the patterns of community supply of antimicrobials from community pharmacies during the COVID-19 pandemic in five cities of Russia. In a cross-sectional study, a random sample of pharmacies reported all episodes of antimicrobials supply during a one-week period. Patterns of supply (age and gender of customer, drug name and formulation, prescription availability, indication, etc.) were analyzed. Altogether, 71 pharmacies took part in the study and 5270 encounters were recorded. In total, 4.2% of visits resulted in supply of more than one antimicrobial agent and 5.2% were for parenteral formulations. The rate of prescription-based purchase in participated cities varied from 40.5 to 99.1%. Systemic antibiotics and antivirals accounted for the majority of supplies (60.5 and 26.3%, respectively). Upper respiratory tract infections were reported as the indication for antimicrobials usage in 36.9% of cases, followed by skin and soft tissue infections (12.1%) and urinary tract infections (8.7%); COVID-19 accounted for 8.4% of all supplies. Amoxicillin with clavulanic acid, azithromycin and amoxicillin were indicated as the top three antimicrobials purchased for upper respiratory tract infections, and azithromycin, umifenovir and levofloxacin were the top three for COVID-19. In general, a high rate of drugs dispensing without prescription was revealed. Antibiotics for systemic use remained the most common antimicrobials, whereas presumably viral upper respiratory tract infections were the main reason for their purchase. COVID-19 infection itself was responsible for a small proportion of the supply of antimicrobial agents, but systemic antibiotics accounted for more than a half of supplies.
A Bidirectional LSTM-RNN and GRU Method to Exon Prediction Using Splice-Site Mapping
Authors: CANATALAY Peren Jerfi , Ucan Osman Nuri
Published: April 2022

Deep Learning techniques (DL) significantly improved the accuracy of predictions and classifications of deoxyribonucleic acid (DNA). On the other hand, identifying and predicting splice sites in eukaryotes is difficult due to many erroneous discoveries. To address this issue, we propose a deep learning model for recognizing and anticipating splice sites in eukaryotic DNA sequences based on a bidirectional Long Short-Term Memory (LSTM) Recurrent Neural Network (RNN) and Gated recurrent unit (GRU). The non-coding introns of the gene are spliced out, and the coding exons are joined during the splicing of the original mRNA transcript. This bidirectional LSTM-RNN-GRU model incorporates intron features in order of their length constraints, beginning with splice site donor (GT) and ending with splice site acceptor (AG). The performance of the model improves as the number of training epochs grows. The best level of accuracy for this model is 96.1 percent.
Modeling of Geophysical Flows through GPUFLOW
Authors: Cappello Annalisa , Bilotta Giuseppe , Ganci Gaetana
Published: April 2022

We present a new model called GPUFLOW for the modeling and simulation of geophysical flows. GPUFLOW, which is based on the cellular automaton paradigm, features a physical model for the thermal and rheological evolution of lava flows (including temperature-dependent emissivity and cooling by radiation and air convection), support for debris flows without thermal dependency, a parallel implementation on graphic processing units (GPUs), and a simpler and computationally more efficient solution to the grid bias problem. Here, we describe the physical–mathematical model implemented in GPUFLOW and estimate the influence of input data on the flow emplacement through different synthetic test cases. We also perform a validation using two real applications: a debris flow that occurred in July 2006 in the Dolomites (Italy) and the December 2018 lava flow from the Etna volcano. GPUFLOW’s reliability prediction is accomplished by fitting the simulation with the actual flow fields, obtaining average values between ~55% and 75%.
A New Approach for Environmental Risk Assessments of Living Modified Organisms in South Korea
Authors: Yoo Su-Hyang , Jung Young Jun , Lee Jung Ro
Published: April 2022

As the development and use of living modified organisms (LMOs) steadily increase, new risk assessment methods that reflect domestic natural ecosystems are being developed. Although LM plants are fundamentally necessary for environmental risk assessment, the introduced gene products and LMO proteins can replace transgenic plants. However, their use is problematic because of instability and indirect assessment data issues. This study proposes a risk assessment tool and scheme for introducing LMO proteins into genetically modified crops. The agroinfiltration method for transient LMO gene expression in plants is a practical tool which can be used to rapidly verify the putative risks of LMO proteins against insects using an LM crop mimic plant with a stably expressed LMO protein. This study used Nicotiana tabacum leaves, which transiently but stably expressed the insecticidal LMO protein Vip3Aa, for LMO risk assessments against Spodoptera litura. The Vip3Aa protein was stably expressed for 5 d in the agroinfiltrated plants, and the protein was active against target insects for environmental LMO risk assessments. In the toxicity evaluation of Vip3Aa-expressing plants against S. litura, the number of deaths was higher in the Vip3Aa-infiltrated N. tabacum-fed group than that in the recombinant Vip3Aa-fed group. In addition, the cumulative number of deaths in the infiltration leaf-fed group was approximately 12-fold higher than that in the protein-fed group under low dosage conditions. This study aimed to develop a transient expression model which can be used to evaluate whether the overall risk of LMO protein is acceptable for use. These results support the usefulness of the transient expression model using an agroinfiltration method as a rapid risk validation tool for LMO proteins against herbivorous insects before producing transgenic plants.
Microalgal Proteins and Bioactives for Food, Feed, and Other Applications
Authors: Lucakova Simona , Branyikova Irena , Hayes Maria
Published: April 2022

Microalgae are a known source of proteins, prebiotics, lipids, small molecules, anti-oxidants and bioactives with health benefits that can be harnessed for the development of functional foods, feeds, cosmeceuticals and pharmaceuticals. This review collates information on the supply, processing costs, target markets and value of microalgae, as well as microalgal proteins, lipids, vitamins and minerals. It discusses the potential impact that microalgae could have on global food and feed supply and highlights gaps that exist with regards to the use of microalgal proteins and ingredients as foods and supplements.
Flow Analysis of PM/NOX Aftertreatment System for Emergency Generator
Authors: Park Giyoung , Bang Hyowon , Lee Seangwock
Published: April 2022

Emergency generators normally use diesel engines. The generators need to conduct weekly no-load operation inspections to ensure stable performance in emergency situations. In particular, the generators with large diesel engines mainly use rectangle-type filter substrates. To minimize hazardous emissions generated by generators, optimizing the reduction efficiency through computational fluid dynamics (CFD) analysis of flow characteristics of particulate matter (PM)/NOX reduction system is important. In this study, we analyzed internal flow by CFD, which is difficult to confirm by experimental method. The main factors in our numerical study are the changes of flow uniformity and back pressure. As a result, the flow distribution characteristics according to the cross-sectional shape are similar at high engine loads. Spraying urea in the reverse direction increases static pressure, greatly improving flow uniformity. Raising the selective catalyst reduction (SCR) diffuser angle to 30 degrees improves both back pressure and flow uniformity characteristics, and when the porosity increases, both flow uniformity and back pressure decrease.
Experimental Analysis on Fatigue Life Assessment of Dissimilar Aluminum Alloys Weld Joints under Four-Point Rotating Bending Condition
Authors: Hashir Muhammad , Rehman Tauseef-ur , Kanti Praveen , Javaid Muhammad Yasar , Park Cheol-Woo
Published: April 2022

Industrial applications often require welded joints of dissimilar metals to perform reliably under adverse working conditions. Such conditions demand high resistance to failure modes, such as fatigue, corrosion, and creep. In applications involving intense vibrational and cyclic loading conditions, high strength-to-weight ratio metals, including aluminum, are more vulnerable to fatigue failure. This study investigates the fatigue strength of base metals and tungsten inert gas welded joints of the two most widely used aluminum alloys, AA7075 and AA2024, under four-point rotating bending. For the comparative study, these dissimilar alloys were joined together by using two different filler rods, AA4047 and AA4043, under similar welding conditions. SN curves for all the samples were generated through the experimental iterations. A comparison of different results shows that welded samples have better fatigue strength than the base metals, while, as a filler, AA4047 has better resistance to fatigue fracture than AA4043.
Outlier Reconstruction of NDVI for Vegetation-Cover Dynamic Analyses
Authors: Sun Zhengbao , Wang Lizhen , Chu Chen , Zhang Yu
Published: April 2022

The normalized difference vegetation index (NDVI) contains important data for providing vegetation-cover information and supporting environmental analyses. However, understanding long-term vegetation cover dynamics remains challenging due to data outliers that are found in cloudy regions. In this article, we propose a sliding-window-based tensor stream analysis algorithm (SWTSA) for reconstructing outliers in NDVI from multitemporal optical remote-sensing images. First, we constructed a tensor stream of NDVI that was calculated from clear-sky optical remote-sensing images corresponding to seasons on the basis of the acquired date. Second, we conducted tensor decomposition and reconstruction by SWTSA. Landsat series remote-sensing images were used in experiments to demonstrate the applicability of the SWTSA. Experiments were carried out successfully on the basis of data from the estuary area of Salween River in Southeast Asia. Compared with random forest regression (RFR), SWTSA has higher accuracy and better reconstruction capabilities. Results show that SWTSA is reliable and suitable for reconstructing outliers of NDVI from multitemporal optical remote-sensing images.
Dynamic Viewpoint Selection for Sweet Pepper Maturity Classification Using Online Economic Decisions
Authors: van Essen Rick , Harel Ben , Kootstra Gert , Edan Yael
Published: April 2022

This paper presents a rule-based methodology for dynamic viewpoint selection for maturity classification of red and yellow sweet peppers. The method makes an online decision to capture an additional next-best viewpoint based on an economic analysis that considers potential misclassification and robot operational costs. The next-best viewpoint is selected based on color variations on the pepper. Peppers were classified into mature and immature using a random forest classifier based on principle components of various color features derived from an RGB-D camera. The method first attempts to classify maturity based on a single viewpoint. An additional viewpoint is acquired and added to the point cloud only when it is deemed profitable. The methodology was evaluated using leave-one-out cross-validation on datasets of 69 red and 70 yellow sweet peppers from three different maturity stages. Classification accuracy was increased by 6% and 5% using dynamic viewpoint selection along with 52% and 12% decrease in economic costs for red and yellow peppers, respectively, compared to using a single viewpoint. Sensitivity analyses were performed for misclassification and robot operational costs.
Contactless Vital Sign Monitoring System for In-Vehicle Driver Monitoring Using a Near-Infrared Time-of-Flight Camera
Authors: Guo Kaiwen , Zhai Tianqu , Purushothama Manoj H. , Dobre Alexander , Meah Shawn , Pashollari Elton , Vaish Aabhaas , DeWilde Carl , Islam Mohammed N.
Published: April 2022

We demonstrate a Contactless Vital Sign Monitoring (CVSM) system and road-test the system for in-cabin driver monitoring using a near-infrared indirect Time-of-Flight (ToF) camera. The CVSM measures both heart rate (HR) and respiration rate (RR) by leveraging the simultaneously measured grayscale and depth information from a ToF camera. For a camera-based driver monitoring system (DMS), key challenges from varying background illumination and motion-induced artifacts need to be addressed. In this study, active illumination and depth-based motion compensation are used to mitigate these two challenges. For HR measurements, active illumination allows the system to work under various lighting conditions, while our depth-based motion compensation has the advantage of directly measuring the motion of the driver without making prior assumptions about the motion artifacts. In addition, we can extract RR directly from the chest wall motion, circumventing the challenge of acquiring RR from the near-infrared photoplethysmography (PPG) signal of low signal quality. We investigate the system’s performance in various scenarios, including monitoring both drivers and passengers while driving on highways and local roads. Our results show that our CVSM system is ambient light agnostic, and the success rates of HR measurements on the highway are 82% and 71.9% for the passenger and driver, respectively. At the same time, we show that the system can measure RR on users driving on a highway with a mean deviation of −1.4 breaths per minute (BPM). With reliable HR and RR measurement in the vehicle, the CVSM system could one day be a key enabler to sudden sickness or drowsiness detection in DMS.
Automatic Speech Recognition (ASR) Systems for Children: A Systematic Literature Review
Authors: Bhardwaj Vivek , Ben Othman Mohamed Tahar , Kukreja Vinay , Belkhier Youcef , Bajaj Mohit , Goud B. Srikanth , Rehman Ateeq Ur , Shafiq Muhammad , Hamam Habib
Published: April 2022

Automatic speech recognition (ASR) is one of the ways used to transform acoustic speech signals into text. Over the last few decades, an enormous amount of research work has been done in the research area of speech recognition (SR). However, most studies have focused on building ASR systems based on adult speech. The recognition of children’s speech was neglected for some time, which means that the field of children’s SR research is wide open. Children’s SR is a challenging task due to the large variations in children’s articulatory, acoustic, physical, and linguistic characteristics compared to adult speech. Thus, the field became a very attractive area of research and it is important to understand where the main center of attention is, and what are the most widely used methods for extracting acoustic features, various acoustic models, speech datasets, the SR toolkits used during the recognition process, and so on. ASR systems or interfaces are extensively used and integrated into various real-life applications, such as search engines, the healthcare industry, biometric analysis, car systems, the military, aids for people with disabilities, and mobile devices. A systematic literature review (SLR) is presented in this work by extracting the relevant information from 76 research papers published from 2009 to 2020 in the field of ASR for children. The objective of this review is to throw light on the trends of research in children’s speech recognition and analyze the potential of trending techniques to recognize children’s speech.
A Vision-Based Approach for Autonomous Motion in Cluttered Environments
Authors: Wu Zhenping , Meng Zhijun , Xu Yulong , Zhao Wenlong
Published: April 2022

In order to complete various tasks automatically, robots need to have onboard sensors to gain the ability to move autonomously in complex environments. Here, we propose a combined strategy to achieve the real-time, safe, and smooth autonomous motion of robots in complex environments. The strategy consists of the building of an occupancy grid map of the environment in real time via the binocular system, followed by planning a smooth and safe path based on our proposed new motion-planning algorithm. The binocular system, which is small in size and lightweight, can provide reliable robot position, attitude, and obstacle information, enabling the establishment of an occupancy grid map in real time. Our proposed new algorithm can generate a high-quality path by using the gradient information of the ESDF (Euclidean Signed Distance Functions) value to adjust the waypoints. Compared with the reported motion-planning algorithm, our proposed algorithm possesses two advantages: (i) ensuring the security of the entire path, rather than that of the waypoints; and (ii) presenting a fast calculation method for the ESDF value of the path points, one which avoids the time-consuming construction of the ESDF map of the environment. Experimental and simulation results demonstrate that the proposed method can realize the safe and smooth autonomous motion of the robot in a complex environment in real time. Therefore, our proposed approach shows great potential in the application of robotic autonomous motion tasks.
Airborne and Dermal Collection Methods of Gunshot Residue for Toxicity Studies
Authors: Smith Samuel Cole , Black Oscar Beau , Roper Courtney
Published: April 2022

Gunshot residue (GSR) has potential negative health effects on humans as a result of inhalation and dermal exposure to the chemical and physical characteristics of GSR such as Pb, Sb, Ba, nitrocellulose, nitroglycerine, and particulate size fraction. Filter (size selective) and double-sided tape (non-size selective) samples collected airborne GSR during single and triple firing of a 0.22 caliber revolver. Dermal exposures were considered using hand swabs and de-leading wipes, designed to remove the heavy metals. The samples underwent analysis to investigate physical (morphology, size distribution, zeta potential), chemical (black carbon and element concentrations), and potential to induce oxidative stress (oxidative potential via the dithiothreitol (DTT) assay). All sample types detected Pb concentrations higher than national ambient air standards. The de-leading wipes reduced the metal content on the hands of the shooter for Pb (15.57 ± 12.99 ppb and 3.13 ± 4.95 ppb). Filter samples provided health relevant data for airborne PM2.5 for all of the analysis methods except for GSR morphology. This work identified collection and analysis methods for GSR in an outdoor setting, providing protocols and considerations for future toxicological studies related to inhalation and dermal exposures to particulate GSR. Future studies should investigate the influence of meteorological factors on GSR exposure in an outdoor setting.
Feature-Driven Characterization of Microservice Architectures: A Survey of the State of the Practice
Authors: Söylemez Mehmet , Tekinerdogan Bedir , Kolukısa Tarhan Ayça
Published: April 2022

With the need for increased modularity and flexible configuration of software modules, microservice architecture (MSA) has gained interest and momentum in the last 7 years. As a result, MSA has been widely addressed in the literature and discussed from various perspectives. In addition, several vendors have provided their specific solutions in the state of the practice, each with its challenges and benefits. Yet, selecting and implementing a particular approach is not trivial and requires a broader overview and guidance for selecting the proper solution for the given situation. Unfortunately, no study has been provided that reflects on and synthesizes the key features and challenges of the current MSA solutions in the state of the practice. To this end, this article presents a feature-driven characterization of micro-service architectures that identifies and synthesizes the key features of current MSA solutions as provided by the key vendors. A domain-driven approach is adopted in which a feature model is presented defining the common and variant features of the MSA solutions. Further, a comparative analysis of the solution approaches is provided based on the proposed feature model.
Effects of Velocity Loss Threshold during Resistance Training on Strength and Athletic Adaptations: A Systematic Review with Meta-Analysis
Authors: Hernández-Belmonte Alejandro , Pallarés Jesús G.
Published: April 2022

This study aimed to systematically review the effects of the different velocity loss (VL) thresholds during resistance training (RT) on strength and athletic adaptations. The VL was analyzed as both a categorical and continuous variable. For the categorical analysis, individual VL thresholds were divided into Low-ModVL (≤ 25% VL) or Mod-HighVL (> 25% VL). The efficacy of these VL thresholds was examined using between-group (Low-ModVL vs. Mod-HighVL) and within-group (pre–post effects in each group) analyses. For the continuous analysis, the relationship (R2) between each individual VL threshold and its respective effect size (ES) in each outcome was examined. Ten studies (308 resistance-trained young men) were finally included. The Low-ModVL group trained using a significantly (p ≤ 0.001) lower VL (16.1 ± 6.2 vs. 39.8 ± 9.0%) and volume (212.0 ± 102.3 vs. 384.0 ± 95.0 repetitions) compared with Mod-HighVL. Between-group analyses yielded higher efficacy of Low-ModVL over Mod-HighVL to increase performance against low (ES = 0.31, p = 0.01) and moderate/high loads (ES = 0.21, p = 0.07). Within-group analyses revealed superior effects after training using Low-ModVL thresholds in all strength (Low-ModVL, ES = 0.79–2.39 vs. Mod-HighVL, ES = 0.59–1.91) and athletic (Low-ModVL, ES = 0.35–0.59 vs. Mod-HighVL, ES = 0.05–0.36) parameters. Relationship analyses showed that the adaptations produced decreased as the VL threshold increased, especially for the low loads (R2 = 0.73, p = 0.01), local endurance (R2 = 0.93, p = 0.04), and sprint ability (R2 = 0.61, p = 0.06). These findings prove that low–moderate levels of intra-set fatigue (≤25% VL) are more effective and efficient stimuli than moderate–high levels (> 25% VL) to promote strength and athletic adaptations.
Research on Space-Based Visible Detection for Conical Space Targets
Authors: Xie Dandan , Huang Yawei , Yan Changxiang , Wang Haihong , Xu Anlin
Published: April 2022

We conducted research into the visible light detection of conical space targets and proposed a method to determine the caliber of a space-based detection system. We constructed a three-dimensional conical space target radiation transfer model and analyzed the effect of the phase angle between the solar incident direction, the detector’s bore sight direction, and the conical target inclination on the radiation intensity of the space target received by the detector. Finally, we obtained the threshold caliber which can meet the detection requirements of the system with the system signal-to-noise ratio as the evaluation standard, and we took the SBV sensor as an example to verify that the caliber determination method in this paper is effective.
High Repetition Rate, TEM00 Mode, Compact Sub-Nanosecond 532 nm Laser
Authors: Meng Dongdong , Wang Tianqi , Zhou Mi , Qiao Zhanduo , Liu Xiaolong , Fan Zhongwei
Published: April 2022

As a critical transmitter, compact 532 nm lasers operating on high repetition and short pulse widths have been used widely for airborne or space-borne laser active remote sensing. We developed a free space pumped TEM00 mode sub-nanosecond 532 nm laser that occupied a volume of less than 125 mm × 50 mm × 40 mm (0.25 L). The fundamental 1064 nm laser consists of a passively Q-switched composite crystal microchip laser and an off-axis, two-pass power amplifier. The pump sources were two single-emitter semiconductor laser diodes (LD) with 808 nm wavelengths and a maximum continuous wave (CW) power of 10 W each. The average power of the fundamental 1064 nm laser was 1.26 W, with the laser operating at 16 kHz repetition rates and 857 ps pulse widths. Since the beam distortion would be severe in microchip lasers due to the increase in heat load, in order to obtain a high beam quality of 532 nm, the beam distortion in our experiment amplifying the fundamental laser was compensated by adjusting the distribution of the pumping beam. Furthermore, in the critical phase matching (CPM) regime for the second harmonic generation (SHG), a Type I LiB3O5 (LBO) crystal obtained 770 ps, a beam quality of M2 < 1.2, and a 16 kHz pulse output at 532 nm, which was better than 0.6 W average power.
A Comprehensive Review of Computer Vision in Sports: Open Issues, Future Trends and Research Directions
Authors: Naik Banoth Thulasya , Hashmi Mohammad Farukh , Bokde Neeraj Dhanraj
Published: April 2022

Recent developments in video analysis of sports and computer vision techniques have achieved significant improvements to enable a variety of critical operations. To provide enhanced information, such as detailed complex analysis in sports such as soccer, basketball, cricket, and badminton, studies have focused mainly on computer vision techniques employed to carry out different tasks. This paper presents a comprehensive review of sports video analysis for various applications: high-level analysis such as detection and classification of players, tracking players or balls in sports and predicting the trajectories of players or balls, recognizing the team’s strategies, and classifying various events in sports. The paper further discusses published works in a variety of application-specific tasks related to sports and the present researcher’s views regarding them. Since there is a wide research scope in sports for deploying computer vision techniques in various sports, some of the publicly available datasets related to a particular sport have been discussed. This paper reviews detailed discussion on some of the artificial intelligence (AI) applications, GPU-based work-stations and embedded platforms in sports vision. Finally, this review identifies the research directions, probable challenges, and future trends in the area of visual recognition in sports.
Efficient Cross-Chain Transaction Processing on Blockchains
Authors: Wang Wenqi , Zhang Zhiwei , Wang Guoren , Yuan Ye
Published: April 2022

Blockchain has received great attention in academia and industry due to its decentralization and immutability. From the perspective of transaction processing, blockchain is a distributed shared ledger and database with the characteristics of decentralization, traceability, and transparency. These features ensure the security of blockchain’s reliability. However, because a blockchain network requires complex consensus verification between users, it causes problems such as a high cost of data exchange and a low system throughput. Such problems are aggravated when executing a cross-chain transaction, as it is particularly important to ensure the atomicity and isolation of transactions across the blockchain. Considering this, in this paper, we propose the cross-chain transaction processing flow of EOVPC and efficient transaction processing based on version control. Different from the existing cross-chain transaction approaches based on locking, we propose optimistic approaches in which the updated data can be used immediately, with a rolling back procedure that guarantees atomicity. We conducted extensive experiments, which show that our approaches can improve the throughput and success rate significantly.
Cyberattack Path Generation and Prioritisation for Securing Healthcare Systems
Authors: Islam Shareeful , Papastergiou Spyridon , Kalogeraki Eleni-Maria , Kioskli Kitty
Published: April 2022

Cyberattacks in the healthcare sector are constantly increasing due to the increased usage of information technology in modern healthcare and the benefits of acquiring a patient healthcare record. Attack path discovery provides useful information to identify the possible paths that potential attackers might follow for a successful attack. By identifying the necessary paths, the mitigation of potential attacks becomes more effective in a proactive manner. Recently, there have been several works that focus on cyberattack path discovery in various sectors, mainly on critical infrastructure. However, there is a lack of focus on the vulnerability, exploitability and target user profile for the attack path generation. This is important for healthcare systems where users commonly have a lack of awareness and knowledge about the overall IT infrastructure. This paper presents a novel methodology for the cyberattack path discovery that is used to identify and analyse the possible attack paths and prioritise the ones that require immediate attention to ensure security within the healthcare ecosystem. The proposed methodology follows the existing published vulnerabilities from common vulnerabilities and exposures. It adopts the common vulnerability scoring system so that base metrics and exploitability features can be used to determine and prioritise the possible attack paths based on the threat actor capability, asset dependency and target user profile and evidence of indicator of compromise. The work includes a real example from the healthcare use case to demonstrate the methodology used for the attack path generation. The result from the studied context, which processes big data from healthcare applications, shows that the uses of various parameters such as CVSS metrics, threat actor profile, and Indicator of Compromise allow us to generate realistic attack paths. This certainly supports the healthcare practitioners in identifying the controls that are required to secure the overall healthcare ecosystem.
A Cross-Country European Efficiency Measurement of Maritime Transport: A Data Envelopment Analysis Approach
Authors: Nguyen Phi-Hung , Nguyen Thi-Ly , Nguyen Thi-Giang , Nguyen Duc-Thinh , Tran Thi-Hoai , Le Hong-Cham , Phung Huong-Thuy
Published: April 2022

Maritime transport, which includes shipping and port operations, is the fundamental basis of international trade and globalization. In transportation management, efficiency is critical for verifying performance and proposing the best countermeasure to meet predetermined goals. Various efforts in this field have been made to solve this problem satisfactorily. However, the significant proportion of conventional approaches are based on long-term observations and professional expertise, with only a few exceptions based on practice-based historical data. Data Envelopment Analysis (DEA) is a non-parametric technique for analyzing various output and input variables parallelly. The efficiency of maritime transport in European countries is explored using a two-stage DEA approach based on Malmquist and Epsilon-Based Measure (EBM). First, the Malmquist model analyses countries’ total productivity growth rates and their breakdown into technical efficiency (catch-up) and technology change (frontier-shift). Second, the EBM model is used to determine the efficiency and inefficiency of the maritime transportation systems in each European country. Apart from identifying the best-performing countries in specific areas over the study period (2016–2019), the results highlight that the gap in applying the EBM method to maritime transport has been successfully closed and that the emerging paradigm, when combined with the Malmquist model, can be a sustainable and appropriate evaluation model for other research areas.