bluuebunny/crossref_metadata_2025 huggingface dataset:
A Model-Driven Approach for Solving the Software Component Allocation Problem
Authors: Al-Azzoni Issam , Blank Julian , Petrović Nenad
Published: December 2021

The underlying infrastructure paradigms behind the novel usage scenarios and services are becoming increasingly complex—from everyday life in smart cities to industrial environments. Both the number of devices involved and their heterogeneity make the allocation of software components quite challenging. Despite the enormous flexibility enabled by component-based software engineering, finding the optimal allocation of software artifacts to the pool of available devices and computation units could bring many benefits, such as improved quality of service (QoS), reduced energy consumption, reduction of costs, and many others. Therefore, in this paper, we introduce a model-based framework that aims to solve the software component allocation problem (CAP). We formulate it as an optimization problem with either single or multiple objective functions and cover both cases in the proposed framework. Additionally, our framework also provides visualization and comparison of the optimal solutions in the case of multi-objective component allocation. The main contributions introduced in this paper are: (1) a novel methodology for tackling CAP-alike problems based on the usage of model-driven engineering (MDE) for both problem definition and solution representation; (2) a set of Python tools that enable the workflow starting from the CAP model interpretation, after that the generation of optimal allocations and, finally, result visualization. The proposed framework is compared to other similar works using either linear optimization, genetic algorithm (GA), and ant colony optimization (ACO) algorithm within the experiments based on notable papers on this topic, covering various usage scenarios—from Cloud and Fog computing infrastructure management to embedded systems, robotics, and telecommunications. According to the achieved results, our framework performs much faster than GA and ACO-based solutions. Apart from various benefits of adopting a multi-objective approach in many cases, it also shows significant speedup compared to frameworks leveraging single-objective linear optimization, especially in the case of larger problem models.
EV Charging in Case of Limited Power Resource
Authors: Rasolonjanahary Manan’Iarivo Louis , Bingham Chris , Schofield Nigel , Bazargan Masoud
Published: December 2021

In the case of the widespread adoption of electric vehicles (EV), it is well known that their use and charging could affect the network distribution system, with possible repercussions including line overload and transformer saturation. In consequence, during periods of peak energy demand, the number of EVs that can be simultaneously charged, or their individual power consumption, should be controlled, particularly if the production of energy relies solely on renewable sources. This requires the adoption of adaptive and/or intelligent charging strategies. This paper focuses on public charging stations and proposes methods of attribution of charging priority based on the level of charge required and premiums. The proposed solution is based on model predictive control (MPC), which maintains total current/power within limits (which can change with time) and imparts real-time priority charge scheduling of multiple charging bays. The priority is defined in the diagonal entry of the quadratic form matrix of the cost function. In all simulations, the order of EV charging operation matched the attributed priorities for the cases of ten cars within the available power. If two or more EVs possess similar or equal diagonal entry values, then the car with the smallest battery capacitance starts to charge its battery first. The method is also shown to readily allow participation in Demand Side Response (DSR) schemes by reducing the current temporarily during the charging operation.
Simplification of Administrative Procedures through Fully Automated Decision-Making: The Case of Norway
Authors: Weitzenboeck Emily M.
Published: December 2021

Norway has a high degree of digitalisation. In the public sector, there is a long tradition of automation of parts of case management. This includes automation of cases where a public sector body makes a so-called individual administrative decision, that is, a decision made in the exercise of public authority through which the rights or duties of one or more specified private persons are determined. In the last five years, various amendments to public sector legislation were proposed by a number of government departments and agencies in Norway to ensure that the relative administrative agency has a legal basis to carry out fully automated individual decisions. This is challenging both from an administrative law and from a data protection law standpoint. Among the main reasons for the move towards fully automated legal decision-making that are mentioned in the preparatory works to the proposed amendments are greater efficiency in decision-making, equal treatment of citizens and a claim that such decisions will be less prone to error than human decisions. This paper examines this trend in Norway and identifies the statutes and regulations that have been amended or are in the process of being amended. It analyses the measures specified in these amendments to safeguard the individual party’s rights, freedoms and legitimate interests. Finally, it discusses the tightrope that must be walked to safeguard important administrative law principles and rules such as protection from arbitrary decisions, the audi alternam partem rule and the right under the European Union’s General Data Protection Regulation not to be subject to fully automated decisions.
Controller Fatigue State Detection Based on ES-DFNN
Authors: Liang Haijun , Liu Changyan , Chen Kuanming , Kong Jianguo , Han Qicong , Zhao Tiantian
Published: December 2021

The fatiguing work of air traffic controllers inevitably threatens air traffic safety. Determining whether eyes are in an open or closed state is currently the main method for detecting fatigue in air traffic controllers. Here, an eye state recognition model based on deep-fusion neural networks is proposed for determination of the fatigue state of controllers. This method uses transfer learning strategies to pre-train deep neural networks and deep convolutional neural networks and performs network fusion at the decision-making layer. The fused network demonstrated an improved ability to classify the target domain dataset. First, a deep-cascaded neural network algorithm was used to realize face detection and eye positioning. Second, according to the eye selection mechanism, the pictures of the eyes to be tested were cropped and passed into the deep-fusion neural network to determine the eye state. Finally, the PERCLOS indicator was combined to detect the fatigue state of the controller. On the ZJU, CEW and ATCE datasets, the accuracy, F1 score and AUC values of different networks were compared, and, on the ZJU and CEW datasets, the recognition accuracy and AUC values among different methods were evaluated based on a comparative experiment. The experimental results show that the deep-fusion neural network model demonstrated better performance than the other assessed network models. When applied to the controller eye dataset, the recognition accuracy was 98.44%, and the recognition accuracy for the test video was 97.30%.
Rope-Hook Recovery Controller Designed for a Flying-Wing UAV
Authors: Deng Zhao , Bing Fuqiang , Guo Zhiming , Wu Liaoni
Published: December 2021

Due to the complexity of landing environments, precision guidance and high-precision control technology have become key to the rope-hook recovery of shipborne unmanned aerial vehicles (UAVs). The recovery process was divided into three stages and a reasonable guidance strategy had been designed for them, respectively. This study separated the guidance and control issues into an outer guidance loop and an inner control loop. The inner loop (attitude control loop) controled the UAV to follow the acceleration commands generated by the outer loop (trajectory tracking loop). The inner loop of the longitudinal controller and the lateral controller were designed based on active disturbance rejection control (ADRC), which has strong anti-interference ability. In the last phase, the outer loop of the longitudinal controller switched from a total energy control system (TECS), which greatly decoupled the altitude channel and speed channel, to the proportional navigation (PN) guidance law, while the outer loop of lateral controller switches from the proportional control law based on the L1 guidance law, which can reduce the tracking error and deviation, to the PN guidance law, which considerably enhances the tracking precision. Finally, the simulation data and flight test data show that the controller has strong robustness and good tracking precision, which ensures safe rope-hook recovery.
Soybean (Glycine max (L.) Merr.) Growth, Yield, and Nodulation in the Early Transition Period from Conventional Tillage to Conservation and No-Tillage Systems
Authors: Adamič Sergeja , Leskovšek Robert
Published: December 2021

Soybean (Glycine max (L.) Merr.) is the most important protein crop globally, with its cultivation area in Europe on the increase. To investigate how alternative tillage systems affect soybean growth, yield performance, and nitrogen fixation capacity in the early conversion period from conventional tillage to conservation and no-tillage practices, a field study was conducted in 2020 under the humid central European climatic conditions of Slovenia. A complete randomized block design with four repetitions was used for the three different tillage systems (conventional, conservation, and no-tillage). The results show that the majority of the studied soybean growth parameters (e.g., plant density, nodes per plant, and shoot and root dry matter) and the yield components (e.g., pods per plant, and 100-seed mass) were greatest for the reference conventional tillage system. The conventional system also showed significantly greater dry nodule mass (p < 0.01) and proportion of large-sized nodules (>4 mm) on both the tap root (p < 0.05) and the lateral roots (p < 0.001). A positive linear correlation between nitrogen content and nodule production in the roots also suggested increased nitrogen fixation for the conventional system. The less intensive conservation and no-tillage systems resulted in significantly greater soil compaction, which negatively affected early plant establishment and resulted in significantly decreased plant densities. Despite the large differences in plant stands and individual plant performances, no significant differences were seen for dry seed yields between these tillage systems. Dry seed yields for the conventional and conservation systems were 4.54 and 4.48 t ha−1, respectively, with only minor (non-significant) yield reduction for the no-tillage system, at 4.0 t ha−1. These data show that soybean cultivation in the early transition period to less intensive tillage systems have no major yield losses under these less suitable agro-climatic conditions if correct crop and weed management measures are implemented.
Effect of Muscle Extract and Graphene Oxide on Muscle Structure of Chicken Embryos
Authors: Bałaban Jaśmina , Zielińska Marlena , Wierzbicki Mateusz , Ostaszewska Teresa , Fajkowska Magdalena , Rzepakowska Małgorzata , Daniluk Karolina , Sosnowska Malwina , Chwalibog André , Sawosz Ewa
Published: December 2021

The effects of CEME and it complex with GO injected in ovo on the growth and development of chicken embryo hindlimb muscle were investigated. First, the preliminary in vitro study on primary muscle precursor cell culture obtained from a nine-day-old chicken embryo was performed to assess toxicity (MTT assay) of CEME, GO (100 ppm) and it complex with different concentrations (1, 2, 5, and 10 wt.%). The effect on cell proliferation was investigated by BrdU assay. CEME at concentrations 1–5% increased cell proliferation, but not the complex with GO. In vitro cytotoxicity was highest in 10% and GO groups. Next, the main experiment with chicken embryos was performed with CEME, GO and it complex injected in ovo on day one of embryogenesis. On day 20 of embryogenesis survival, morphological development, histological structure of the muscle, and biochemical parameters of blood serum of the embryos were measured. No negative effect on mortality, body weight, or biochemistry of blood after use of CEME or GO-CEME complexes was observed. Interestingly, the slight toxicity of GO, observed in in vitro studies, was not observed in vivo. The use of CEME at the levels of 2% and 5% improved the structure of the lower limb muscle by increasing the number of cells, and the administration of 2% CEME increased the number of nuclei visible in the stained cross-section of the muscle. The complex GO-CEME did not further improve the muscle structure. The results indicate that CEME can be applied as an in ovo enhancer of muscle development in broilers.
Effect of Actin Alpha Cardiac Muscle 1 on the Proliferation and Differentiation of Bovine Myoblasts and Preadipocytes
Authors: Li Anqi , Su Xiaotong , Tian Yuan , Song Guibing , Zan Linsen , Wang Hongbao
Published: December 2021

Actin Alpha Cardiac Muscle 1 (ACTC1) gene is a differentially expressed gene screened through the co-culture system of myoblasts-preadipocytes. In order to study the role of this gene in the process of proliferation and differentiation of bovine myoblasts and preadipocytes, the methods of the knockdown, overexpression, and ectopic expression of ACTC1 were used in this study. After ACTC1 knockdown in bovine myoblasts and inducing differentiation, the sizes and numbers of myotube formation were significantly reduced compared to the control group, and myogenic marker genes—MYOD1, MYOG, MYH3, MRF4, MYF5, CKM and MEF2A—were significantly decreased (p < 0.05, p < 0.01) at both the mRNA and protein levels of myoblasts at different differentiation stages (D0, D2, D4, D6 and D8). Conversely, ACTC1 overexpression induced the inverse result. After ectopic expression of ACTC1 in bovine preadipocytes and induced differentiation, the number and size of lipid droplets were significantly higher than those of the control group, and the expression of adipogenic marker genes—FABP4, SCD1, PPARγ and FASN—were significantly increased (p < 0.05, p < 0.01) at the mRNA and protein levels of preadipocytes at different differentiation stages. Flow cytometry results showed that both the knockdown and overexpression of ACTC1 inhibited the normal cell cycle of myoblasts; however, ectopic expression of ACTC1 in adipocytes induced no significant cell cycle changes. This study is the first to explore the role of ACTC1 in bovine myogenesis and lipogenesis and demonstrates that ACTC1 promotes the differentiation of bovine myoblasts and preadipocytes, affecting the proliferation of myoblasts.
Assessing the Genetic Background and Selection Signatures of Huaxi Cattle Using High-Density SNP Array
Authors: Ma Jun , Gao Xue , Li Junya , Gao Huijiang , Wang Zezhao , Zhang Lupei , Xu Lingyang , Gao Han , Li Hongwei , Wang Yahui , Zhu Bo , Cai Wentao , Wang Congyong , Chen Yan
Published: December 2021

Huaxi cattle, a specialized beef cattle breed in China, has the characteristics of fast growth, high slaughter rate, and net meat rate, good reproductive performance, strong stress resistance, and wide adaptability. In this study, we evaluated the genetic diversity, population structure, and genetic relationships of Huaxi cattle and its ancestor populations at the genome-wide level, as well as detecting the selection signatures of Huaxi cattle. Principal component analysis (PCA) and phylogenetic analysis revealed that Huaxi cattle were obviously separated from other cattle populations. The admixture analysis showed that Huaxi cattle has distinct genetic structures among all populations at K = 4. It can be concluded that Huaxi cattle has formed its own unique genetic features. Using integrated haplotype score (iHS) and composite likelihood ratio (CLR) methods, we identified 143 and 199 potentially selected genes in Huaxi cattle, respectively, among which nine selected genes (KCNK1, PDLIM5, CPXM2, CAPN14, MIR2285D, MYOF, PKDCC, FOXN3, and EHD3) related to ion binding, muscle growth and differentiation, and immunity were detected by both methods. Our study sheds light on the unique genetic feature and phylogenetic relationship of Huaxi cattle, provides a basis for the genetic mechanism analysis of important economic traits, and guides further intensive breeding improvement of Huaxi cattle.
Phytogenic Feed Additives in Poultry: Achievements, Prospective and Challenges
Authors: Abdelli Nedra , Solà-Oriol David , Pérez José Francisco
Published: December 2021

Phytogenic feed additives have been largely tested in poultry production with the aim to identify their effects on the gastrointestinal function and health, and their implications on the birds’ systemic health and welfare, the production efficiency of flocks, food safety, and environmental impact. These feed additives originating from plants, and consisting of herbs, spices, fruit, and other plant parts, include many different bioactive ingredients. Reviewing published documents about the supplementation of phytogenic feed additives reveals contradictory results regarding their effectiveness in poultry production. This indicates that more effort is still needed to determine the appropriate inclusion levels and fully elucidate their mode of actions. In this frame, this review aimed to sum up the current trends in the use of phytogenic feed additives in poultry with a special focus on their interaction with gut ecosystem, gut function, in vivo oxidative status and immune system as well as other feed additives, especially organic acids.
Correction: Rydén et al. Physiological and Clinical Responses in Pigs in Relation to Plasma Concentrations during Anesthesia with Dexmedetomidine, Tiletamine, Zolazepam, and Butorphanol. Animals 2021, 11, 1482
Authors: Rydén Anneli , Jensen-Waern Marianne , Nyman Görel , Olsén Lena
Published: December 2021

Text Correction [...]
L-Arginine Supplementation for Nulliparous Sows during the Last Third of Gestation
Authors: Rodrigues Gustavo de Amorim , Júnior Dante Teixeira Valente , Soares Marcos Henrique , Silva Caroline Brito da , Fialho Fernanda Abranches , Barbosa Lívia Maria dos Reis , Neves Mariana Machado , Rocha Gabriel Cipriano , Duarte Marcio de Souza , Saraiva Alysson
Published: December 2021

We evaluated the effects of L-arginine supplementation during the last third of gestation on molecular mechanisms related to skeletal muscle development of piglets and litter traits at birth. Twenty-three nulliparous sows averaging 205.37 ± 11.50 kg of body weight were randomly assigned to the following experimental treatments: control (CON), where pregnant sows were fed diets to meet their nutritional requirements; arginine (ARG), where sows where fed CON + 1.0% L-arginine. Skeletal muscle from piglets born from sows from ARG group had greater mRNA expression of MYOD (p = 0.043) and MYOG (p ≤ 0.01), and tended to present greater mRNA expression (p = 0.06) of IGF-2 gene compared to those born from CON sows. However, there were no differences (p > 0.05) in the histomorphometric variables of fetuses’ skeletal muscle. The total weight of born piglets, total weight of born alive piglets, piglet weight at birth, coefficient of variation of birth weight, and the incidence of intrauterine growth restriction (IUGR) piglets did not differ between groups. No stillborn piglets (p < 0.01) were verified in the ARG sows compared to CON group. The blood levels of estradiol (p = 0.035) and urea (p = 0.03) were higher in ARG sows compared to those from the CON group. In summary, our data show that arginine supplementation of nulliparous sows at late gestation enhance mRNA expression of key myogenic regulatory factors, which likely contribute to improve animal growth rates in later stages of development.
Sustainability of Rearing System Using Multicriteria Analysis: Application in Commercial Poultry Production
Authors: Rocchi Lucia , Cartoni Mancinelli Alice , Paolotti Luisa , Mattioli Simona , Boggia Antonio , Papi Francesco , Castellini Cesare
Published: December 2021

The aim of the present study was to develop a multicriteria model for the comparison of three commercial poultry farms: organic with Ross 308 genotype (OR), organic with Naked Neck genotype (ONN) and a conventional system (C), which represents the most common commercial farming system. A model based on multicriteria decision analysis was developed, considering for the first time the One Welfare approach in an operational manner, including three dimensions: human, environmental and animal welfare. The three alternatives demonstrated different performances, according to the different dimensions considered. In particular, the two organic systems performed better for human welfare and animal welfare, with relevant differences due to the genetic strains used. Conventional rearing performed better for the environment index due to the method chosen. The multicriteria analysis showed that the organic system performed better overall than the conventional system. In particular, the use of an adapted Slow Growing (SG) strain positively affected the final rank, mainly by reducing welfare problems and producing good economic and social performance. The stability of the results was verified by performing a sensitivity analysis, specifically a weight stability analysis, which confirmed the strength of results.
How Housing Conditions Determine the Welfare of Pigs
Authors: Ludwiczak Agnieszka , Skrzypczak Ewa , Składanowska-Baryza Joanna , Stanisz Marek , Ślósarz Piotr , Racewicz Przemysław
Published: December 2021

Humans who care for pigs prefer an environment that not only allows the pigs to express their natural behaviors but also limits the development of aggression and stereotypes. Most of the behavioral and health problems encountered by pigs in barren, conventional conditions are solved by alternative housing systems. However, it is not known whether these systems are advantageous in terms of the performance of pigs. In this work, we review the effects of housing systems on pigs’ behaviors and performance, which are among the major indicators of the welfare of these animals. Research results point out that outdoor systems are more ideal for sows and fatteners than buildings. Nonetheless, outdoor housing is associated with two major effects in both groups: increased activity due to environmental exploration and higher space allowance, and increased incidence of injuries compared to indoor systems. Sows are more active when housed in groups, but they experience an increased frequency of injuries. According to the literature, group-housed sows give birth to healthy piglets with good daily weight gains. The difference in the fattening and slaughter performance of pigs raised indoors vs. outdoors remains unclear, and the results reported so far are inconsistent. Outdoor systems seem to be associated with a higher incidence of osteochondrosis and lesions of elbow and hock joints, whereas indoor systems cause a greater degree of body soiling in pigs. Based on the reviewed literature, it may be concluded that outdoor housing helps to solve behavioral issues in pigs but leads to other problems in pig production.
Effect of Breeding Heavier Romney Ewe Lambs at Seven Months of Age on Lamb Production and Efficiency over Their First Three Breeding Seasons
Authors: Haslin Emmanuelle , Corner-Thomas Rene A. , Kenyon Paul R. , Pettigrew Emma J. , Hickson Rebecca E. , Morris Steve T. , Blair Hugh T.
Published: December 2021

This experiment examined the effect of breeding heavier ewe lambs on lamb production and their efficiency over their first three breeding seasons. Two groups of ewe lambs were bred at seven months of age at an average pre-breeding live weight of either 47.9 ± 0.36 kg (heavy; n = 135) or 44.9 ± 0.49 kg (control; n = 135). Ewe live weight, number of lambs born and weaned, and lamb live weight were recorded until 39 months of age, and efficiency was calculated for each ewe. Although the number and lamb weaning weight did not differ between treatments over three years, when data were pooled, heavier ewe lambs at breeding weaned a greater number of lambs over the three-year period. The total lamb weaning weight over the three-year period increased by 2% for each additional kilogram at ewe lamb breeding. Breeding heavier ewe lambs had no effect on efficiency. These results suggest that although breeding heavier ewe lambs had a positive effect on lamb production over the three-year period, it had no effect on efficiency. Before final recommendations can be made, lifetime performance and longevity to five years of age of heavier ewe lambs at breeding are required.
Adoption of Precision Technologies by Brazilian Dairy Farms: The Farmer’s Perception
Authors: Silvi Rebeca , Pereira Luiz Gustavo R. , Paiva Claudio Antônio V. , Tomich Thierry R. , Teixeira Vanessa A. , Sacramento João Paulo , Ferreira Rafael E. P. , Coelho Sandra G. , Machado Fernanda S. , Campos Mariana M. , Dórea João Ricardo. R.
Published: December 2021

The use of precision farming technologies, such as milking robots, automated calf feeders, wearable sensors, and others, has significantly increased in dairy operations over the last few years. The growing interest in farming technologies to reduce labor, maximize productivity, and increase profitability is becoming noticeable in several countries, including Brazil. Information regarding technology adoption, perception, and effectiveness in dairy farms could shed light on challenges that need to be addressed by scientific research and extension programs. The objective of this study was to characterize Brazilian dairy farms based on technology usage. Factors such as willingness to invest in precision technologies, adoption of sensor systems, farmer profile, farm characteristics, and production indexes were investigated in 378 dairy farms located in Brazil. A survey with 22 questions was developed and distributed via Google Forms from July 2018 to July 2020. The farms were then classified into seven clusters: (1) top yield farms; (2) medium–high yield, medium-tech; (3) medium yield and top high-tech; (4) medium yield and medium-tech; (5) young medium–low yield and low-tech; (6) elderly medium–low yield and low-tech; and (7) low-tech grazing. The most frequent technologies adopted by producers were milk meters systems (31.7%), milking parlor smart gate (14.5%), sensor systems to detect mastitis (8.4%), cow activity meter (7.1%), and body temperature (7.9%). Based on a scale containing numerical values (1–5), producers indicated “available technical support” (mean; σ2) (4.55; 0.80) as the most important decision criterion involved in adopting technology, followed by “return on investment—ROI” (4.48; 0.80), “user-friendliness” (4.39; 0.88), “upfront investment cost” (4.36; 0.81), and “compatibility with farm management software” (4.2; 1.02). The most important factors precluding investment in precision dairy technologies were the need for investment in other sectors of the farm (36%), the uncertainty of ROI (24%), and lack of integration with other farm systems and software (11%). Farmers indicated that the most useful technologies were automatic milk meters systems (mean; σ2) (4.05; 1.66), sensor systems for mastitis detection (4.00; 1.57), automatic feeding systems (3.50; 2.05), cow activity meter (3.45; 1.95), and in-line milk analyzers (3.45; 1.95). Overall, the concerns related to data integration, ROI, and user-friendliness of technologies are similar to those of dairy farms located in other countries. Increasing available technical support for sensing technology can have a positive impact on technology adoption.
Scaled Experiment of the Detonation Control System for the High-Speed Penetration on Concrete
Authors: Yan Huan , Gao Shiqiao , Jin Lei
Published: December 2021

The design scheme and fabrication technology of the detonation control system for the high-speed deep penetration need to be tested for reliability and effectiveness through shooting range tests. However, the shooting range tests of the high-speed deep penetration are so demanding and expensive that it is difficult for the detonation control system to be tested many times. This paper focuses on penetration characteristics of the detonation control system to put forward a laboratory-scaled experiment method with the low impact velocity. Independent parameters of projectile and target affecting the penetration characteristics are effectively analyzed and extracted. A multi-parameter programming method of the scaled experiment for high-speed deep penetration is established. By adjusting the key parameters, the loading conditions of the scaled experiment can be obtained, which can get the comparable deceleration curve with those of the high-speed deep penetration. Finally, the extreme working environment for the detonation control system in the high-speed deep penetration is simulated through the scaled experiment in the laboratory. The scaled experiment method can get the comparable deceleration peak and time history. It is highly economical, and the experimental process is also repeatable, which can provide a reliable reference for the protection design into the projectile.
Experimental Study on the Influence of Water and Cavitation on Propeller Load during Ice-Propeller Milling
Authors: Xu Pei , Wang Chao , Ye Liyu
Published: December 2021

When the ice-class propeller sails in an icy sea, it is affected by external factors such as water, ice, and cavitation, and the process of mutual interference is extremely complicated. In order to study the influence of water and cavitation on propeller load during the ice-propeller milling process, a test platform for ice–water propeller milling action was constructed. The load and cavitation of the propeller and single blade were measured during ice-propeller milling in air and water (atmospheric pressure and decompression conditions). Simultaneously, the changes in the load and bearing force of the propeller and blade were studied at different working conditions. The results show that, in the process of ice–water propeller milling, the direction of the propeller thrust generated by the water is opposite to that of the axial force generated by ice; the combined action of the two causes propeller thrust loss, whereas the combined action of water and ice increases propeller torque. The presence of water increases the thrust, torque, and bearing force of the fluctuating amplitude of the blade. The occurrence of cavitation reduces the thrust and torque of the propeller and blade and increases thrust fluctuating amplitudes while decreasing the tangential force fluctuating amplitude of the blade.
Anti-Psoriatic Effects and IL-22 Targeting Mechanism of Indirubin by Suppressing Keratinocyte Inflammation and Proliferation
Authors: Nguyen Ly Thi Huong , Oh Tae-Woo , Choi Min-Jin , Yang In-Jun , Shin Heung-Mook
Published: December 2021

Indigo naturalis, which is extracted from the leaves and branches of Baphicacanthus cusia (Nees) Bremek, has traditionally been used to treat psoriasis. The current study aimed to examine a new mechanism of the components of indigo naturalis, including indirubin, indigo, and tryptanthrin. The anti-psoriatic effects were assessed by the proliferation biomarkers (Ki67, K16), cell cycle progression, ROS production, and interleukin profiling (ICAM-1, TNF-α, IL-6, and IL-8) in IL-22-treated HaCaT cells. Among the components, indirubin significantly decreased intracellular ROS production and lowered the production of ICAM-1, TNF-α, and IL-6 in IL-22-treated HaCaT cells. Indirubin, indigo, and tryptanthrin could decrease the proportion of Ki67-positive cells, but only indirubin decreased the proportion of cells entering the S phase and suppressed the expression of cyclin D1 and cyclin E1 in IL-22-treated HaCaT cells. Indirubin significantly suppressed the phosphorylation of STAT3 and ERK. In vivo, IL-22 was intradermally injected into mouse ears for six days and topically treated with 0.1% or 1% indirubin. In the IL-22-injected mice, treatment with indirubin inhibited epidermal hyperplasia. Immunohistochemistry and western blot analysis demonstrated the downregulation of K16 expression in psoriatic lesions. These results suggest that indirubin, which is a major component of indigo naturalis, may have therapeutic potential in an IL-22-induced psoriasis model.
Caatinga Albedo Preserved and Replaced by Pasture in Northeast Brazil
Authors: Souza Alcindo Mariano , Santos e Silva Cláudio Moisés , Bezerra Bergson Guedes
Published: December 2021

The caatinga is considered South America’s largest seasonally dry tropical forest (SDTF) and one of the most vulnerable endemic biomes in relation to climate change. The surface albedo in caatinga is relevant to understanding the role of this biome in the climate of the Northeast region of Brazil. Thus, a comparative analysis was conducted between the albedos of preserved and anthropized caatinga (pasture). Data were collected using CNR4-type net radiometers during the dry and rainy seasons. The mean albedo values were higher in the Pasture both in the dry and rainy season, with values of 0.181 and 0.177, respectively. In the caatinga, the mean albedo values were 0.137 in the dry season and 0.146 in the rainy season. The hourly average values for albedo, taken between 6:30 a.m. and 4 p.m., with intervals of 30 min, were also higher in the pasture. For convenience, this study uses local standard time (LST), which is 3 h behind from coordinated universal time (UTC). The greatest dispersions in the frequencies of the mean hourly albedo values occurred in the early morning and late afternoon. Some of the consequences of this study is the confirmation that there is an increase in albedo in caatinga replaced by pasture and this causes a reduction in the net radiation and also the finding that a region where there is adequate pasture management also enables albedo management and from solar radiation. And that further studies can indicate the impacts on temperature and precipitation, especially in warmer periods during the dry season.
Prediction of Air Pollutant Concentration Based on One-Dimensional Multi-Scale CNN-LSTM Considering Spatial-Temporal Characteristics: A Case Study of Xi’an, China
Authors: Dai Hongbin , Huang Guangqiu , Wang Jingjing , Zeng Huibin , Zhou Fangyu
Published: December 2021

Air pollution has become a serious problem threatening human health. Effective prediction models can help reduce the adverse effects of air pollutants. Accurate predictions of air pollutant concentration can provide a scientific basis for air pollution prevention and control. However, the previous air pollution-related prediction models mainly processed air quality prediction, or the prediction of a single or two air pollutants. Meanwhile, the temporal and spatial characteristics and multiple factors of pollutants were not fully considered. Herein, we establish a deep learning model for an atmospheric pollutant memory network (LSTM) by both applying the one-dimensional multi-scale convolution kernel (ODMSCNN) and a long-short-term memory network (LSTM) on the basis of temporal and spatial characteristics. The temporal and spatial characteristics combine the respective advantages of CNN and LSTM networks. First, ODMSCNN is utilized to extract the temporal and spatial characteristics of air pollutant-related data to form a feature vector, and then the feature vector is input into the LSTM network to predict the concentration of air pollutants. The data set comes from the daily concentration data and hourly concentration data of six atmospheric pollutants (PM2.5, PM10, NO2, CO, O3, SO2) and 17 types of meteorological data in Xi’an. Daily concentration data prediction, hourly concentration data prediction, group data prediction and multi-factor prediction were used to verify the effectiveness of the model. In general, the air pollutant concentration prediction model based on ODMSCNN-LSTM shows a better prediction effect compared with multi-layer perceptron (MLP), CNN, and LSTM models.
Elemental Carbon Observed at a Peri-Urban Forest Site near the Seoul Metropolitan Area as a Tracer of Seasonal Haze Occurrence
Authors: Ham Jeeyoung , Suh Inseon , Lee Meehye , Kim Hyunseok , Kim Soyoung
Published: December 2021

In order to identify the seasonal variability and source of carbonaceous aerosols in relation to haze occurrence, organic carbon (OC) and elemental carbon (EC) were continuously measured at the Taehwa Research Forest (TRF) near the Seoul metropolitan area from May 2013 to April 2014. For the entire experiment, the mean OC (5.1 µgC/m3) and EC (1.7 µgC/m3) concentrations of TRF were comparable to those of Seoul, with noticeably higher concentrations in winter and spring than in other seasons, and during haze days (6.6 ± 3.2 and 2.1 ± 1.0 μgC/m3) than during non-haze days (3.5 ± 2.2 and 1.3 ± 0.8 μgC/m3). The seasonal characteristics of OC and EC reveal the various sources of haze, including biomass combustion haze either transported for long distances or, in spring, from domestic regions, the greatest contribution of secondary organic carbon (SOC) in summer, and fossil fuel combustion in winter and fall. In addition, the seasonal OC/EC ratios between haze and non-haze days highlights that the increase in EC was more distinct than that of OC during haze episodes, thus suggesting that EC observed at a peri-urban forest site serves as a useful indicator for seasonally varying source types of haze aerosols in the study region.
Multi-Scale Object-Based Probabilistic Forecast Evaluation of WRF-Based CAM Ensemble Configurations
Authors: Wilkins Andrew , Johnson Aaron , Wang Xuguang , Gasperoni Nicholas A. , Wang Yongming
Published: December 2021

Convection-allowing model (CAM) ensembles contain a distinctive ability to predict convective initiation location, mode, and morphology. Previous studies on CAM ensemble verification have primarily used neighborhood-based methods. A recently introduced object-based probabilistic (OBPROB) framework provides an alternative and novel framework in which to re-evaluate aspects of optimal CAM ensemble design with an emphasis on ensemble storm mode and morphology prediction. Herein, we adopt and extend the OBPROB method in conjunction with a traditional neighborhood-based method to evaluate forecasts of four differently configured 10-member CAM ensembles. The configurations include two single-model/single-physics, a single-model/multi-physics, and a multi-model/multi-physics configuration. Both OBPROB and neighborhood frameworks show that ensembles with more diverse member-to-member designs improve probabilistic forecasts over single-model/single-physics designs through greater sampling of different aspects of forecast uncertainties. Individual case studies are evaluated to reveal the distinct forecast features responsible for the systematic results identified from the different frameworks. Neighborhood verification, even at high reflectivity thresholds, is primarily impacted by mesoscale locations of convective and stratiform precipitation across scales. In contrast, the OBPROB verification explicitly focuses on convective precipitation only and is sensitive to the morphology of similarly located storms.
Assessment of Chemical Fiber Air Filter for General Ventilation
Authors: Li Yanju , Chai Pengchang , Wang Yu , Cheng Zelin
Published: December 2021

Air filters for general ventilation have mainly been used to control the concentration of indoor particulate matter. In this study, the pressure differential, test dust capacity, quality factor and operating life of class F8 pleat–plate and multi-bag type chemical fiber filters were evaluated using an air filter performance test system. The results showed that the resistance increase rate of multi-bag filter (0.49 Pa/g·(cm/s)) was lower than that of pleat–plate filter (1.94 Pa/g·(cm/s)), the quality factor of the multi-bag filter was lower than that of pleat–plate filter, and the dust capacity of the multi-bag filter was much higher than that of the pleat–plate filter. The operating life of the multi-bag filter was 8 times as that of the pleat–plate filter with the measured PM2.5 of outdoor. The energy consumption of the pleat–plate filter was 2.2 times that of the multi-bag filter. Analyzing the electron microscope photos after dust loading, the dust depth of pleat–plate filter into filter material was thinner than that of multi-bag filter. The research results could provide data support for the design optimization and selection of ventilation filters and the treatment of the particulate matter in indoor environments.
A Laboratory Investigation of the Probable Mechanisms of the Action of an Artificial Thunderstorm Cell on Model Aircraft Radomes
Authors: Lysov Nikolay , Temnikov Alexander , Chernensky Leonid , Orlov Alexander , Belova Olga , Kivshar Tatiana , Kovalev Dmitry , Belyakov Mikhail , Voevodin Vadim
Published: December 2021

The results of experimental laboratory investigations of possible mechanisms of the impact of lightning and thunderclouds on aircraft radomes and equipment inside them are presented. An artificial thunderstorm cell of negative polarity and model aircraft radomes with lightning diverter strips have been used. Experiments have shown that the discharge processes in a radome model significantly depend on the magnitude of the charge that accumulates on the inner and outer surfaces of the radome shell. It is established that the accumulation of large-magnitude charges of different signs on the outer and/or inner surface of the radome (up to hundreds of µC/m2) shell leads to a multivariance of the mechanisms of development of discharge processes inside the radome model, along its surface, and in the space near it. Significant influence of the “reverse” discharge from the antenna model under the radome on the types of current impulses recorded on the antennas under impact of the artificial thunderstorm cell is established. Peculiarities of the discharge formation in the radome model when using solid and segmented diverter strips for its protection are revealed. Parameters of the current impulses registered on the diverter strips and the antennas have been determined. Based on the conducted research, the possible mechanisms of the impact of thunderclouds and lightning discharges on radio-transparent aircraft radomes and the equipment inside them are considered.
Oleg Zatsarinny (1953–2021): Memories by His Colleagues
Authors: Bartschat Klaus , Fischer Charlotte Froese , Grum-Grzhimailo Alexei N.
Published: December 2021

A collection of short stories about Oleg Ivanovich Zatsarinny (1953–2021) to whom this Special Issue of Atoms is dedicated.
Explainable COVID-19 Detection on Chest X-rays Using an End-to-End Deep Convolutional Neural Network Architecture
Authors: Chetoui Mohamed , Akhloufi Moulay A. , Yousefi Bardia , Bouattane El Mostafa
Published: December 2021

The coronavirus pandemic is spreading around the world. Medical imaging modalities such as radiography play an important role in the fight against COVID-19. Deep learning (DL) techniques have been able to improve medical imaging tools and help radiologists to make clinical decisions for the diagnosis, monitoring and prognosis of different diseases. Computer-Aided Diagnostic (CAD) systems can improve work efficiency by precisely delineating infections in chest X-ray (CXR) images, thus facilitating subsequent quantification. CAD can also help automate the scanning process and reshape the workflow with minimal patient contact, providing the best protection for imaging technicians. The objective of this study is to develop a deep learning algorithm to detect COVID-19, pneumonia and normal cases on CXR images. We propose two classifications problems, (i) a binary classification to classify COVID-19 and normal cases and (ii) a multiclass classification for COVID-19, pneumonia and normal. Nine datasets and more than 3200 COVID-19 CXR images are used to assess the efficiency of the proposed technique. The model is trained on a subset of the National Institute of Health (NIH) dataset using swish activation, thus improving the training accuracy to detect COVID-19 and other pneumonia. The models are tested on eight merged datasets and on individual test sets in order to confirm the degree of generalization of the proposed algorithms. An explainability algorithm is also developed to visually show the location of the lung-infected areas detected by the model. Moreover, we provide a detailed analysis of the misclassified images. The obtained results achieve high performances with an Area Under Curve (AUC) of 0.97 for multi-class classification (COVID-19 vs. other pneumonia vs. normal) and 0.98 for the binary model (COVID-19 vs. normal). The average sensitivity and specificity are 0.97 and 0.98, respectively. The sensitivity of the COVID-19 class achieves 0.99. The results outperformed the comparable state-of-the-art models for the detection of COVID-19 on CXR images. The explainability model shows that our model is able to efficiently identify the signs of COVID-19.
Effect Mechanism of Electroacupuncture at ST36 on the Injured Extensor Digitorum Longus in the Jumping Rat Model Based on mRNA-Seq Analysis
Authors: Liu Qianqian , Guo Yanwei , Han Rui
Published: December 2021

The key target and regulatory mechanism of electroacupuncture of Zusanli (ST36) on extensor longus muscle injury in a jumping rat model were investigated. To this end, 24 female SD rats were randomly divided into the following four groups: no-treatment control group (NON), 6-week jumping group (J6O), electroacupuncture group after 6-week jumping (J6A), and natural recovery group after 6-week jumping (J6N). After 6 weeks of jumping, in the electroacupuncture group (J6A), electroacupuncture stimulation was applied at Zusanli(ST36) for 20 min per day over the course of 5 days. In the natural recovery group (J6N), rats were fastened with a special apparatus without electroacupuncture stimulation for 20 min at the same time. Transmission electron microscopy, transcriptome sequencing and analysis, Western blotting assay and immunofluorescence staining were performed at the end of our experiment. The recovery effect of J6A rats was more obvious than that of J6N rats and J6O rats as indicated by changes of infiltration of inflammatory cells and morphological structure. Notably, the morphological structure of J6A rats was closer to NON rats in the observation of transmission electron microscopy. CISH/STAT3 regulation was identified by mRNA-seq. The pro-inflammatory response to STAT3 activation was alleviated through up-regulating the expression of CISH protein in J6A rats relative to J6O rats. The level of BAX was decreased and the level of Bcl-2 level was increased in J6A rats relative to J6O rats. Moreover, when compared to J6N rats, the level of Bcl-2 was significantly up-regulated in J6A rats. Increased caspase-3 expression but decreased CDKN2α expression was shown in J6A rats relative to NON rats. These results indicate that the potential mechanism underlying electroacupuncture stimulation of Zusanli (ST36) in repairing the injured extensor digitorum longus following overused jumping may be attributed to CISH/STAT3 regulation of proteins associated with inflammation, apoptosis, and proliferation.