bluuebunny/crossref_metadata_2025 huggingface dataset:
Oral myiasis associated with drug induced gingival hyperplasia – a rare case report
Authors: Gadda Rohit B. , Agrawal Ankush , Kumar SN Santosh , Rothe Tushar Manohar
Published: September 2021

Introduction: Myiasis (Greek: myi = fly) refers to infestation of living tissues of humans and animals by Dipterous eggs or larvae. Incidence of oral myiasis is comparatively lesser than that of cutaneous myiasis. We report a rare case of oral myiasis of anterior maxilla associated with drug induced gingival enlargement. Observation: We report a rare case of oral myiasis of anterior maxilla with amlodipine induced gingival enlargement in a sixty-two-year-old male with history of hypertension, hemiplegia and diabetes mellitus. Patient was mouth breather and presented with poor oral hygiene. Generalized gingival hyperplasia was observed. Multiple maggots were observed in the ulcerated areas on maxillary anterior alveolus. The maggots were mechanically removed with curettage after application of turpentine oil. Cleaning and debridement of the wound was done. After one month follow-up there was complete healing of the lesion. Maintenance of oral hygiene and gingivectomy as indicated was planned for this patient. Conclusion: Clinical significance of presented case is its rarity of association with drug induced gingival hyperplasia and typical presence of multiple predisposing factors. This case report provides interesting information about predisposing factors, clinical features and management of oral myiasis that could help clinicians in the diagnosis and management of this condition.
Digitale Technologien, forensische Altersdiagnostik und wissenswerte
Updates
Authors: Jung B. A.
Published: September 2021

Sehr geehrte Kolleginnen und Kollegen!

In dieser Ausgabe haben wir für Sie einen bunten Strauß aus
gemischten Themenfeldern zusammengestellt. Den Auftakt bilden „Digitale
Technologien“ und wissenswerte Fakten zur „forensischen
Altersdiagnostik“. Darüber hinaus geben die Autoren Seeberger
und Weickum wichtige Hinweise zur zahnärztlichen-chirurgischen
Vorbereitung und Unterstützung kieferorthopädischer
Maßnahmen. Johan Wölber berichtet über den Einfluss der
Ernährung auf die Mundgesundheit und Christian Hirsch trägt
wissenswerte Fakten zu Wurzelresorptionen permanenter Zähne im Kindes-
und Jugendalter zusammen.
Epithetik 3D – Digitale Wege für die Gesichtsprothetik
Authors: Unkovskiy Alexey , Keutel Constanze , Spintzyk Sebastian , Hüttig Fabian
Published: September 2021

Die Versorgung mit Gesichtsprothesen (Epithesen) ist eine technische wie auch psychologische Herausforderung– für die betroffenen Patienten wie auch die Epithetiker und Behandler. Der technologische Fortschritt bei digitalen Prozessketten von der Erfassung, über die Weiterverarbeitung bis hin zur Fertigung erlaubt es in diesem Teilgebiet erhebliche Verbesserungen zu ermöglichen. So können kontaktlose Abformungen von Defekten die Belastungen für den Patienten reduzieren und das digitale Design die Laufzeit und Reproduzierbarkeit für die Versorger verbessern. Der 3D-Druck stellt in Aussicht, Prototypen bis hin zu fertigen Prothesen verlässlich fertigen zu können, wobei abschließende Individualisierungen auch langfristig noch nötig sein werden. Der vorliegende Artikel beschreibt die Grundzüge der Versorgung, den derzeitigen Entwicklungsstand und zukünftige Möglichkeiten bei der Versorgung von gesichtsversehrten Patienten.
Versorgung junger Patienten mit kraniofazialen Anomalien mittels digitaler Technologie im Tübinger Konzept
Authors: Xepapadeas Alexander B. , Aretxabaleta Maite , Spintzyk Sebastian , Wiechers Cornelia , Krimmel Michael , Weise Christina
Published: September 2021

Für die Behandlung junger Patienten mit kraniofazialen Anomalien ist die Entwicklung eines digitalen Workflows für das Design von Apparaturen auf Basis von intraoralen Scans die erste Hürde. Um die Sicherheit dieser Patientengruppe zu gewährleisten, werden potenzielle additiv oder subtraktiv gefertigte Materialien getestet und die Genauigkeit in vitro gemessen.
Einfluss der Ernährung auf die Mundgesundheit
Authors: Wölber Johan
Published: September 2021

Das Ernährungsverhalten von Homo sapiens hat sich im Laufe der Menschheitsgeschichte stark verändert und stellt mittlerweile immer häufiger einen Grund für Erkrankungen dar. Dieser Beitrag möchte zeigen, welche Auswirkungen moderne Ernährung auf die Munderkrankungen hat und welche Ernährungsstrategien für Mundgesundheit genutzt werden können.
Improved Synthesis of the Antitubercular Agent SQ109
Authors: Kolocouris Antonios , Stampolaki Marianna
Published: September 2021

We present here an improved procedure for the preparation of the promising antitubercular drug SQ109 that is currently in phase Ib/III of clinical trials against Mycobacterium tuberculosis. We investigated and tested the literature synthetic procedure that enables the development of structure–activity relationships and report the observed inconsistencies as well as presenting improvements or novelties for the more efficient preparation of SQ109. Most significantly we applied a novel reduction step of the aminoamide precursor using Me3SiCl­/LiAlH4 under mild conditions. These findings are important for research groups investigating the efficacy of this drug and analogues in academia and industry.
Justice beyond repair: Negative Dialectics and the politics of guilt and atonement
Authors: Cucharo Stephen
Published: September 2021

This article draws out a critical, yet under-appreciated political theme in Adorno’s Negative Dialectics, namely his emphasis on guilt and atonement. First, the article assesses how Adorno’s Marxism allows him to think justice and guilt beyond the familiar legalistic frame. Second, the article reconstructs Adorno’s treatment of guilt as a distinctly political capacity to imagine one’s boundedness and indebtedness to others, and the affective engine enabling us to engage in a political ethic distinct from familiar categories of reparation. Third, the article shows how the themes of guilt and atonement give us a more complete picture of Negative Dialectics. This inquiry also intervenes in contemporary debates regarding the political status and emancipatory potential latent within guilt-feelings, and claims Adorno gives us a path forward to imagine the relation between guilt and politics in a novel way.
Laser Safety in LIGO
Authors: King Peter
Published: September 2021

The Laser Interferometer Gravitational Wave Observatory (LIGO) Project is a multiwavelength laser environment. Wavelengths from the visible to the far infrared are used in the interferometer and its diagnostic subsystems. This chapter describes some laser safety considerations and practices within the LIGO Project.
Anthropogenic impacts on Late Holocene land-cover change and floristic biodiversity loss in tropical southeastern Asia
Authors: Zheng Zhuo , Ma Ting , Roberts Patrick , Li Zhen , Yue Yuanfu , Peng Huanhuan , Huang Kangyou , Han Ziyun , Wan Qiuchi , Zhang Yaze , Zhang Xiao , Zheng Yanwei , Saito Yoshiki
Published: September 2021

Significance

Palaeoecological analysis reveals that the expansion of rice agriculture in southern China and Southeast Asia around 2,000 y ago caused widespread deforestation and biodiversity changes in tropical and subtropical forests. Tropical forests, with the highest level of plant diversity and concentration of endemic species, suffered greater decline of arboreal richness than forests in subtropical and temperate areas. In subtropical ecosystems, total plant richness increased, despite arboreal decline, possibly thanks to the flourishing of herbs in an opening landscape. The disappearance of
Glyptostrobus
in southeastern Asia provides a case study as to how early rice agriculture endangered an endemic species by causing losses of its natural habitats, with prehistoric land-use changes leaving a clear legacy for today’s landscapes and species compositions.
Understanding West Africa’s informal workers as working class
Authors: McDermott Joshua Lew
Published: September 2021

Informal workers in Africa are very often portrayed as primarily self-employed entrepreneurs and unemployed individuals largely excluded from capitalism, and thus insulated from class analysis and class dynamics. Drawing on a case study of informal workers in Sierra Leone, the article challenges this dominant understanding, arguing that informal workers experience the reality of class relations and that their material lives are shaped by, and help to shape, broader dynamics of capital accumulation. The research applies a holistic class analysis rooted in Marxist and feminist thought, arguing for an understanding of informal workers, including even small-scale ‘self-employed’ individuals, as workers exploited by, and opposed to the interests of, capital. In so doing, it challenges the simple understandings of working class as existing only and exclusively through formalised wage work, in favour of a more complex and inductive understanding of the reality of global capitalism, highlighting the relevance of class, value and exploitation to the lived reality of informal workers in Africa.
Revisiting isocurvature bounds in models unifying the axion with the inflaton
Authors: Ballesteros Guillermo , Ringwald Andreas , Tamarit Carlos , Welling Yvette
Published: September 2021

Axion scenarios in which the spontaneous breaking of the
Peccei-Quinn symmetry takes place before or during inflation, and in
which axion dark matter arises from the misalignment mechanism, can
be constrained by Cosmic Microwave Background isocurvature
bounds. Dark matter isocurvature is thought to be suppressed in
models with axion-inflaton interactions, for which axion
perturbations are assumed to freeze at horizon crossing during
inflation. However, this assumption can be an oversimplification
due to the interactions themselves. In particular,
non-perturbative effects during reheating may lead to a dramatic
growth of axion perturbations. We perform lattice calculations in
two models in which the Peccei-Quinn field participates in
inflation. We find that the growth of axion perturbations is such
that the Peccei-Quinn symmetry is restored for an axion decay
constant f
A ≲ 1016–1017 GeV, leading to an
over-abundance of dark matter, unless f
A ≲ 2 × 1011 GeV. For f
A ≳ 1016–1017 GeV we still find
a large growth of axion perturbations at low momentum, such that a
naive extrapolation to CMB scales suggests a violation of the
isocurvature bounds.
Ground shear strain value based on microseismic data in Oebelo, Kupang NTT
Authors: Mala H U , Lalus H F , Nanlohy P , Elake A Y
Published: September 2021

Information the ground shear strain in an area are very important. Quantitatively, this characteristic is reflected in the value of shear strain. This value provides an illustration of the ability of the soil layer to vibrate, stretch or shift even broken during an earthquake. The potential of vibrating and stretching of the soil is not only influenced by the magnitude and hypocenter but also the geological conditions of the local area. Geological characteristics in the form of dominant frequency values and amplification factors were obtained through the HVSR method using microseismic waves. The study was conducted in Oebelo, Kupang with a distribution of 52 points of microseismic measuring. Its parameters are used to calculate the seismic vulnerability index value and PGA value. These two values are used to determine the shear strain value at each measuring point. The results showed the magnitude of shear strain values was range from 1.5 × 10−2 to 1.6 × 10−1. The highest is located at coordinates 10.111280 S and 123.74180 E, while the area with the lowest at the coordinates 10.115780 S and 123.73960 E. Areas with shear strain values in the range 10−2 to 10−1 above, have dynamic properties are collapse, repeat-effects and speed-effects of loading. Phenomena that will occur are landslides, soil compaction and liquefaction during an earthquake. In the context of risk reduction, it is necessary to avoid areas with high shear strain values for human activities and infrastructure development.
Design of VR application in detection line based on industrial robot for optical routers
Authors: Zhang Bei
Published: September 2021

In this study, an automated detection line for optical routers is designed. The output of the production line is evaluated and optimized on the basis of the product lifecycle management (PLM) data. The VR technology is used to build a 3D virtual reality scene to realize the layout design and planning of industry, while providing functions such as employee training, technological process roaming and interactive experience. Thus, a set of representative transformation schemes for flexible manufacturing cells can be obtained.
Trip-GhostNet for Hyperspectral Image Classification
Authors: Zhang Zitong , Hu Xiaoqing , Wang Siqing , Kang Lei , Ma Qiaoyu
Published: September 2021

The classification of hyperspectral remote sensing images (HSI) is an important task in the processing and application of hyperspectral images. Convolutional neural network (CNN) has significant advantages in the extraction and fusion of hyperspectral image spectrum and spatial features, so it has become a common method in the field of HSI classification. However, the spectral domain feature redundancy of hyperspectral images is very high, and the spatial domain feature structure is complex, which makes CNN more time-consuming and higher memory requirements in the feature extraction process. Based on this problem, lightweight networks with fewer parameters have gradually become the main application method in the field of HSI classification. In order to reduce the computational complexity of deep feature extraction and take into account the shallow features, a high-order nonlinear Ghost module is proposed on the basis of the original Ghost linear transformation module. Furthermore, in view of the independent characteristics of each dimension of HSI, a Trip-GhostNet is proposed, which simultaneously extracts and fuses features from three dimensions in a lightweight manner. According to the distribution characteristics of HSI, the influence of attention embedding methods in the high-order Ghost module of each branch on the feature extraction is compared and analyzed. The results show that the proposed model can reduce model calculations and improve classification accuracy, and is suitable for HSI classification problems.
Research on Algorithm of fighter landing gear in bad video image
Authors: Tang Miao , Fang Wei , Yan Wenjun , Ling Qing
Published: September 2021

The retracted and retracted state of landing gear is a problem that needs to be paid close attention to in the landing process of fighter. The traditional visual observation is easy to be affected by the climate environment. Aiming at the problems of small target, low definition and difficult detection of fighter landing gear in bad video images, a YOLOv4 target detection algorithm based on image enhancement is proposed to detect fighter landing gear. In order to improve the accuracy of landing gear detection, ACE algorithm is first applied to the video image to enhance the video image, then the main feature extraction network of YOLOv4 is used to extract the feature information, and K-means clustering algorithm is used to cluster and analyze the number and aspect ratio dimension of target candidate frames. Experiments on the dataset show that the detection accuracy after image enhancement reaches 88.12%, which is 1.19% higher than the original image; The recall rate reached 73.44%, an increase of 4.17%; The value of mAP reached 82.65%, an increase of 1.08%.
Infrared small target detection method based on multi-scale feature fusion
Authors: Wang Fang , Li Chuanqiang , Wu Bo , Yu Kun , Jin Chan
Published: September 2021

Infrared small target detection is widely used in aerial target detection and tracking system because of its long detection distance and strong anti-jamming ability. Aiming at the shortcomings of the current infrared small target detection algorithm, such as low precision rate and high false alarm rate when dealing with complex background. In this paper, we propose an end-to-end infrared small target detection model (called MFSSD) based on multi-scale feature fusion. Considering the trait of the targets, we propose a feature fusion module by using a refinement and fusion feature map method, and improve the correlation of different channels through the SP Module. The experimental results of three different sequences of infrared image detection show that the average detection accuracy of the MFSSD algorithm in infrared small target detection is as high as 87.8%. Compared with the traditional multi-scale feature fusion detection algorithm, both the precision rate and the recall rate have been significantly improved.
Optical-imaging detection of apple sugar content based on OpenCv and Pytorch
Authors: Hu Shuhe , Yang Yuping
Published: September 2021

Based on the Rayleigh scattering and Mie scattering, a scattering model in the apple pulp tissue is theoretically established, and the relationship between the sugar content of the apple pulp and the light intensity distribution of the diffuse reflection image is derived.Firstly, a homemade reflection-collection system has been applied to collect the scattering light intensity distribution of 133 apples with different varieties, skin colors, and sugar contents. According to acquired optical images 133 original images are processed based on OpenCv, and the appropriate region is extracted to recreate the image set, and the image features of the image set are derived with the aid of the denoising self-encoding neural network for data dimensionality reduction. The image feature and the recorded fructose content table are made into a data set, which is divided into a training set and a test set at a ratio of 3:1. Finally, through the training of the neural network, the non-destructive prediction of the apple sugar content is successfully achieved within a certain range.
Academic literature recommendation technology based on two-layer attention network
Authors: Deng Hanyang , Tang Shiping
Published: September 2021

Recently, academic literature recommendation for learners has become an important topic. Recently deep learning based models are used in literature recommendations, which follow a similar Embedding&MLP paradigm. However, in the base model and its follow-up model Deep Interest Network (DIN), users only have to click or not click on items, limiting the expression of users' specific interests. Therefore, we propose a two-layer attention model (BIH) based on DIN. BIH adds specific behaviors to the user behavior sequence and adds a behavior attention layer, which can learn the expression of user interests more accurately. Experiments on a public dataset and users' behavior logs of academic literature demonstrate the effectiveness of proposed approaches, which achieve superior performance on both Macro-F1 and Micro-F1 compared with the base model and DIN.
Visual comparison and analysis of the speed and strength of different versions of Beethoven piano sonata no. 8 (op. 13no.1), 1st moveme nt based on Vmus.net
Authors: Liu Shuqing
Published: September 2021

This paper is based on Vmus.net platform, using music visualization analysis technology.Through three experiments, combined with the relevant music background information of Beethoven piano sonata no. 8 (op. 13no.1), 1st movement the audio of four pianists were selected as the research content, and the elastic expansion and strength fluctuation of music speed were compared and analyzed from different perspectives of micro and macro.In this way, we can understand the characteristics of personalized processing and performance of Beethoven piano sonata no. 8 (op. 13no.1), 1st movement by different players in different periods.
A Metal Artifact Reduction Method with Bone Segmentation for CBCT Images
Authors: Zhang Songze , Jiang Benxiang , Shi Hongjian
Published: September 2021

Nowadays, CBCT images become popular and are widely used in the dental diagnosis. The image quality is related to the accuracy of diagnosis and treatment. When metal objects such as the dental implants are present in CBCT scanning, the metal artifacts will appear and decrease the image quality. In order to reduce the metal artifacts, this paper proposes a metal artifact reduction method for the dental CBCT images. This method is based on inpainting the sinogram and mainly has three innovations. First, this method forward-projects only the region around the metal implants. Second, the bones in the forward projection region are segmented and their intensity values are set to zero before the forward projection. Finally, this method computes an image to directly correct the original CBCT image, this correction image is the back projection of the difference between the interpolated sinogram and the original sinogram. The proposed method reduces the metal artifacts and improves the image quality, it may potentially increase the diagnosis value of the CBCT images corrupted by the metal artifacts.
Comparative analysis of 2D-PCA based dimensionality reduction and feature extraction
Authors: Zhang Kai , Hu Xiaoqing , Kang Lei , Ma Qiaoyu , Zhang Xin
Published: September 2021

The complex spectral and spatial characteristics of hyperspectral remote sensing images (HSI) lead to higher time-consuming in classification task. To address this question, we introduced the 2D-PCA dimensionality reduction method of linear mapping in the two-dimensional spatial domain on the basis of linear dimensionality reduction in the spectral domain, thereby compressing the complex spatial structure information of HSI into a limited low-dimensional space, and realizing space-spectrum dimensionality reduction and information fusion. The experimental results on three classic data sets of Salinas, Tea Farm, and Indian Pines show that 2D-PCA has a strong ability to condense and compress spatial structure characteristics. Compared with popular deep learning frameworks such as CNN and Mixer-MLP, conventional machine learning models based on 2D-PCA have significant advantages in terms of computing time under the premise of controllable accuracy loss, which makes 2D-PCA a promising method for dimensionality reduction and feature expression in hyperspectral pixel-wise classification.
Prediction of Aircraft Aerodynamic Coefficient Based on Data-Driven Method
Authors: Liu Chang , Wang Xingbo , Liu Xinghua
Published: September 2021

To identify the aerodynamic coefficient of aircraft that cannot be directly measured in actual flight, in this paper, the problem of aerodynamic coefficient identification has been solved with the rigid body three-degree-of-freedom model using aircraft dynamics model based approaches. And based on the data-driven method to predict the aerodynamic coefficients, based on radial basis function neural network (RBFNN) with particle swarm optimization (PSO) has been used to achieve the task. Taking the external disturbance and the noise of flight data into account, a section of flight data of the XXX aircraft is preprocessed. The aerodynamic coefficients are identified based on the pre-processed flight data, and the prediction results of the aerodynamic coefficients of the above methods are analyzed, which proves the effectiveness of using the data-driven method to predict the aerodynamic coefficients.
Feature investigation on the ROP machine learning model using realtime drilling data
Authors: Cao Jie , Gao Jiaxuan , Jiao Tong , Xiang Ruiyi , Pang Yanyan , Li Tiantai
Published: September 2021

To meet the demand for reducing drilling costs in petroleum engineering, improving drilling efficiency is one of the main objectives in field operations. Highly accurate prediction of ROP is an essential basis for improving drilling efficiency and reducing development cycle time. However, realtime prediction of the Rate of Penetration (ROP) is not straightforward, affected by a number of operational and mechanical parameters. The interactions between these parameters also complicated the analysis and modeling ROP. In the presented study, we apply the Feature Engineering approach to analyze the features affecting ROP according to their relevance and relative importance. In addition, the input features are reduced from 14, manually selected based on physical relevance, to optimized 8. Then the model is retrained again for comparing the accuracy of the two prediction models. As a result, it is concluded that by reducing the input of low impact features, the model is substantially simplified, while there are only insignificant accuracy changes.
Prediction model of needle valve body extrusion grinding process based on PSO-SVR
Authors: Xie Ruibin , Yang Shuzhen , Sun Chenzhe , Yu Tao
Published: September 2021

The needle valve body is one of the core components of the diesel engine injection system, there is a complicated non-linear relationship between process parameters and process effects in its extrusion and grinding process, and it is difficult to establish specific mathematical expressions to describe the process rules. Therefore, this paper adopts support vector regression (SVR) establish a needle valve body extrusion grinding process model, and uses flow coefficient and grinding efficiency as dual output prediction targets. The particle swarm optimization algorithm (PSO) with better global search ability is introduced to optimize and improve the model. The results show that the optimized model has a smaller error between the predicted value and the actual value of the data, and the prediction accuracy is significantly improved. The model can reflect the process law of the needle valve body extrusion and grinding process to a certain extent, and it can provide certain guidance for selecting process parameters in the extrusion and grinding process.
Emotion Prediction of EEG Signals based on 1D Convolutional Neural Network
Authors: Gao Jiaman , Yang Chengyi , Liu Feng , Qi Jiayin
Published: September 2021

Artificial intelligence has been widely used in the field of biological signal recognition. However, most researches use deep learning to classify emotions, which has limitations in its application in the medical field. To this end, this paper proposes a one-dimensional convolutional neural network (1D-CNN) model for regression tasks. After we standardize, transform and slice the data, we divide the training set, validation set, and test set at a ratio of 8:1:1, and feed the data into the neural network for training to achieve emotion prediction. Experiments on the DEAP dataset show that the model we built has good performance for emotion prediction, which provides new insights for the medical field. The source codes are available at https://github.com/gjm-web/1D-CNN.
A Novel Text Ensemble Clustering Based on Weighted Entropy Filtering Model
Authors: Shen Qiaoyun , Qiu Yican
Published: September 2021

Text clustering is one of the important technical bases of natural language processing, and ensemble clustering improves the robustness of text clustering. According to the existing research of scholars and experts, the quality and diversity of basic clustering have a great influence on consensus clustering, and it has a particularly significant effect on text clustering. However, there are a few pieces of research aiming at reducing the number of low-quality clustering in ensembles. This paper proposes a novel clustering filtering model based on entropy criteria. The entropy criterion is used to evaluate the uncertainty of each cluster w.r.t. the ensemble. Two indexes are proposed on the basis of the uncertainty of cluster, namely, Clustering Trend Index (CTI) which indicates the contribution of each cluster w.r.t. basic clustering, and Cluster Consistency Index(CCI) which indicates the degree of cluster dispersion in the basic clustering. The proposed clustering filtering model is built on the basis of new weight using two proposed indexes. Thereby, by dropping the low-quality clustering, the percentage of high-quality clustering will increase. A large number of experiments on various real text data sets using optimal thresholds show that the proposed method has greatly improved accuracy and robustness, and is superior to existing ensemble clustering algorithms.
Multi-objective discrete salp swarm optimizer for solving multiple-product U-shaped disassembly line balancing problem
Authors: Li Jiawei , Guo Xiwang , Peng Fangjie , Qi Liang , Qin Shujin
Published: September 2021

The disassembly line balancing problem is one of the most significant methods in handling large quantities of waste electrical and electronic equipment efficiently problems. In this paper, we propose a U-shaped layout disassembly line and set up a mathematical model to maximize the disassembly profit and minimize the disassembly time of hazardous parts. Therefore, an improved Multi-objective Salp swarm algorithm based on Pareto which combines with a stochastic simulation method is proposed to solve such a U-shaped disassembly line balancing problem. Some cases are used to verify the effectiveness of the proposed method. The results show the proposed method can solve the U-shaped disassembly line balancing problem and outdo the other two optimization algorithms: Nondominated Sorting Genetic Algorithm-II (NSGA-II) and Multi-objective Evolutionary Algorithm based on Decomposition (MOEA/D) in the quality of solutions.
Construction of network teaching and research course platform based on multimedia and deep learning
Authors: Shen Xiangping , Ju Tongyao , Yu Jun
Published: September 2021

Today's online courses are widely used. This is also one of the main ways many people pursue learning. With the rapid advancement of China's education reform, people are no longer satisfied with the traditional classroom teaching. With the emergence of deep learning technology, today's university education and other adult education have begun to change to mixed teaching methods. Building a network teaching and research platform based on multimedia and deep learning is a hot topic today. This paper expounds the current situation of traditional curriculum teaching. Finally, it expounds the construction of multimedia network teaching and research course platform.
Effect of stacking sequences on tensile properties of natural fiber hybrid polymer composite
Authors: Ganesh R , Anand P
Published: September 2021

Recent years, researchers have concentrated on eco-friendly materials. In particular natural fiber reinforced composites have an impact on the environment while processing and utilizing such materials. Natural fibers are abundantly available in the world and it is used as reinforcing material into polymers considered replacement of conventional materials in many applications for environmental concern. In this study kenaf and fiber reinforced hybrid composite laminates were fabricated using hand layup technique. with two stacking sequence variant laminate A, laminmate B like sandwiched structure. In both the laminates, skin, core and intermediate layers were varied. Tensile properties of these composite laminates were found experimentally using a UTM machine. For analyzing the elastic behaviour of these laminates, finite element analysis was carried out using Ansys workbench. Experimental results were compared with FEA results. There was high correlation between these results. The results justify the hybridization of kenaf and basalt fiber potential. .this hybrid composites are well suited for aerospace structural applications.
Experimental investigations on mechanical properties of cotton/hemp fiber reinforced epoxy resin hybrid composites
Authors: Mohanavel V , Sathish T , Ravichandran M. , Ganeshan P , Ravi Kumar M.M. , Subbiah Ram
Published: September 2021

In this experiment, epoxy resin, fine hemp fibre, and cotton fibres were combined to create bio-composites. The weight percentages of hemp fibre (0, 10, 20, 30 wt. percent), cotton fibres (35, 25, 15, 5 wt. pewrcent), and epoxy resin have been varied to produce four composite mates. As per ASTM standards, composite specimens were prepared using the water jet machining process. Tensile, flexural, and impact tests were performed on the composite specimens in order to determine their mechanical properties and water absorption behaviour. Composites containing 20 wt.% fine hemp fibre in weight percentage showed significant improvements in tensile properties. Composites containing 30 wt% hemp fibre improve both flexural and impact properties, according to the test results.
Thermal runaway model of high-nickel large format lithium-ion battery under thermal abuse conditions
Authors: Wu S , Bai Y , Luan W , Wang Y , Li W , Wang L , Lu S
Published: September 2021

Battery safe necessitates preventing thermal runaway and its propagation. Aiming at the thermal runaway problem of pure electric vehicle lithium-ion power battery, a thermal runaway model for large-capacity lithium-ion prismatic batteries is developed. Two thermal abuse conditions: hot box and single-side heating are considered in the simulation. Corresponding experiments are conducted to verify the accuracy of the model. The results show that the gas generated by the decomposition of the solid electrolyte interface (SEI) membrane and the anode-solvent reaction triggered the pressure relief valve. The thermal runaway process of single-side heating has a temperature difference of more than 200°C, and thermal runaway may have occurred when the local temperature of the battery is normal. This lays a foundation for subsequent research and system development.
Exploration of Rain Gauge Quality Issues in Northern England
Authors: Fadhel S , Saleh M S
Published: September 2021

The rain gauge, which is the preferred device for rain rate quantification, is susceptible to various types of errors. The problems of inconsistency and incompletion of rainfall time-series, in addition to data quality issues obstruct hydrometeorological analysis. Daily rainfall data from 30 gauges in Northern England were quality controlled by a double quality check procedure for the period 2006–2014 to solve any specific data quality issues. It emerged that fault readings happened only over a few days compared with the high percentage of missing data which could reach years. Thus, factors that impact gauges’ missing data were inspected. It was found that snowfalls, land cover-land use and bird distribution are the dominant factors that malfunctioning the rain gauge for long time periods, often producing successive missing days that could be extended months in total. However, when the missing data happened on separate days, then it seemed that high winds related with light rainfall resulted in drifting away the rainfall from the rain gauge and thus caused missing data. Moreover, the rainfall itself was not one of the major factors to malfunction the gauge, because the values of missed rainfall were not quite extreme to do this.
Biodiversity of the Ilmen Klint
Authors: Abdushaeva Ya M , Mazirov M A
Published: September 2021

The Ilmen Klint is a geologically formed landmark located in the Shimsky and Starorussky districts of the Novgorod region. Its location area is the western part of the southern shore of Lake Ilmen and covers the delta of the Lovat and Shelon rivers. A characteristic feature of the soils of the banks of the Psizha river is the presence of laminated dense crystalline yellowish-brown limestones. In the upper part of the Ilmen Klint, near Buregi village, brown limestones have formed. The modern vegetation cover of the Ilmen Klint has resulted from a long historical process and now continues to undergo changes. The main role in this is played by the human, their economic activities. In 2001, the Ilmen Klint was accorded the status of a Specially Protected Natural Area (SPNA) of the Novgorod region in order to preserve and study its natural diversity and maintain its ecological balance. The carried out floristic studies made it possible to describe natural habitats with a rich floristic composition and equity participation of Lathyrus pratensis L., Medicago falcata L.: Medicago lupulina L., and Anthyllis macrocephala L. species. The meadows and outcrop areas of the Ilmen Klint are characterized by a high diversity of rare species with certain patterns of meadow community development. At a high coastal slope level, there is a dry meadow with a herb-foxtail community. In addition, the participation of crop wild relatives (CWR) in natural plant communities of the Ilmen Klint territory is considered. Species of the Fabaceae L family are the main source of CWR here. Human well-being depends on the conservation of biodiversity and biological resources, particularly plant resources.
Ensuring the Environmental Safety of Large Cities Based on an Innovative Approach to Predicting Atmospheric Air Pollution
Authors: Andreeva E S , Lipovitskaya I N , Lazareva E O , Andreev S S , Zharkova M G
Published: September 2021

Sustainable development of territories should be based on ensuring sufficient quality of the air basin. Air quality management, in turn, is based on adequate predictive models that allow the development of a number of measures to improve its quality. In this regard, the article is devoted to the discussion of issues of ensuring the environmental safety of territories, including rural ones, on the basis of the innovative approach developed by the authors to the implementation of the forecast of the air quality of the lower layer of the atmosphere. The choice of the object of study–the city of St. Petersburg–is connected with the fact that the city has a network of posts for environmental monitoring of the state of the air environment, providing up-to-date information for making a forecast scheme. As a result of the conducted research, the authors identified groups of meteorological and synoptic characteristics, as well as formed databases of hydrometeorological data and series of concentrations of a number of impurities for the period from 2006 to 2014. It is assumed that the successful application of the developed scheme for predicting the quality of atmospheric air will ensure the environmental safety of the population of urban and rural areas.
Theoretical Studies of a Centrifugal Pneumatic Separator with Horizontal Air Flow
Authors: Chernyakov A V , Koval V S , Begunov M A , Algazin D N , Boytsov K A
Published: September 2021

The article is devoted to the study of the motion of grain heap particles along the cylindrical surface of the separator. This article substantiates the relevance of post-harvest grain processing in the agro-industrial complex, proposes a design of a centrifugal pneumatic separator with a horizontal air flow, and describes the process of its operation. A mathematical model is obtained for the motion of a grain heap particle along the cylindrical surface of a grain separator with a centrifugal horizontal air flow.
Influence of Hydrological Conditions on the Meliorative Features of the Soils of the Novgorod Region
Authors: Druzhnova M P , Dmitruk N G
Published: September 2021

The article is devoted to the problem of drainage and conditions of soil moisture in the Novgorod region; the solution of this problem is associated with the definition of reclamation measures in agricultural land use. The article gives a characteristic of drained areas, identified based on the conditions of their moisture, type of nutrition, depth of groundwater, granulometric composition and filtration coefficient of rocks, height of the terrain and, accordingly, the degree of soil moisture, and proposed reclamation measures aimed at increasing their fertility.
Peculiriaties of Growing Breeding Replacement Young Animals on the Farms of Ayrshire and Black Pied Cattle
Authors: Emelyanov E G , Shestakov V M
Published: September 2021

The high genetic potential of productivity and a similar level of animal feeding underlie the intensive technology of rearing young animals for dairy cattle breeding. The realization of the genetic potential of dairy productivity of livestock largely depends on the efficiency of rearing young animals. Therefore, proper feeding of livestock is one of the main factors contributing to the maximum realization of this potential of animals. The conducted studies have shown that the breeding plants of the studied region successfully solve the issues of intensive cultivation of repair young animals. The increase in live weight of heifers allows for the first insemination at 16–17 months with the corresponding live weight. However, in the whole region, the data on the growth and development of heifers are significantly inferior to the indicators of breeding plants and the first insemination is carried out at 19 months and older. As a result of the conducted research, a plan for the growth of repair young animals was developed and the average daily live weight gains for the growing periods were recommended. The demand of reared young cattle for metabolic energy and crude protein is calculated.
Investigation of Crystallization Process of Lactose in Milk Serum Permeate
Authors: Evdokimov I A , Gridin A S , Volodin D N , Kulikova I K , Slozhenkina M I
Published: September 2021

One of the main factors determining physicochemical and structural properties of the dry permeate of spray drying is lactose which is present in permeate as a basic phase. If lactose is in the β-form in a dry powder, the powder easily absorbs moisture from the atmosphere during storage, causing agglutination, clumping, and caking of the product. Prevention of negative consequences associated with increased hygroscopicity, is ensured by the directed crystallization of lactose in a condensed product before spray drying. The purpose of this investigation was to study the crystallization process of lactose in permeate under industrial conditions when using various seed materials. Results of the studies showed that the type of a crystal forming agentdoes not affect the size and shape of lactose crystals and the level of lactose crystallization. Seed material is of critical significance as it will ensure both a high level of crystallization and homogenous crystals which, in general, leads to an increase in melting temperature, due to a decrease in the proportion of amorphous lactose, as well as improves the drying process.
Study of Effect of Mixed Culture of Probiotic Microorganisms on the Efficiency of Fermentative Hydrolysis of Soybean Processing Products
Authors: Kalashnikova O B , Sukhikh S A , Kriger O V , Babich O O , Laricheva K N
Published: September 2021

Soybean meal (SM) is the main protein source for animals. However, certain anti-nutritional factors such as trypsin inhibitor, glycinin, raffinose, stachyose and others reduce its nutritional value, and inhibit the growth and development of animals. Fermentation of soybean meal is an economical alternative which improves nutritional properties of soybean meal due to both biodegradation of anti-nutritional factors, proteins, fibers, and probiotic and prebiotic production, which can subsequently improve taste and digestibility of nutrients. The purpose of this work is to study the effect of a selected consortium of probiotic microorganisms on the composition of fermented soybean meal (FSM). Experiments showed that the introduction of a mixed culture including strains Bacillus subtilis B7046, Aspergillus niger F1270, Saccharomyces cerevisiae Y4659, Lactobacillus plantarum K9 B5466 led to an increase in the content of easily digestible protein in the fermented soybean meal and a decrease in the content of anti-nutrional factors.
Technological Platform for the Best Available Technologies for Processing Universal Agricultural Raw Materials
Authors: Khramtsov A G , Borisenko A A , Borisenko L A , Voblikova T V
Published: September 2021

The article discusses the historically formed spiral cycles of development of the technological platform for the best available whey processing technologies. The characteristics of the stages of development repeated at each cycle, reflecting the level of scientific and technological progress in this area are presented. The main technological trends and concepts of milk whey processing in the near, medium and longer term are considered. It is shown that in the future, breakthrough achievements in food technologies will be based on the results of digital transformation of production, the introduction of innovative technologies for digital modeling and design, quantum computing, robotic automation and additive technologies.
Productivity Potential of Ayrshire Cattle and Its Implementation in Conditions of Agro-Volok LLC, Novgorod Region
Authors: Kondratieva T N
Published: September 2021

Dairy cattle breeding continues to be the leading field of agriculture. Along with the productivity growth of animals, milk production and profitability, it is if great importance to improve quality, reduce to minimum mechanical and bacterial contamination, improve technological properties, as well as reduce losses in the course of production, primary processing and temporary storage. In the course of a particular study it was shown that the modernization of domestic breeds, the improvement of their productive and technological characteristics on the basis of the use of the gene pool of the best world breeds are of fundamental importance for cattle breeding intensification. The Finnish Ayrshire cattle, along with the Holstein, Dutch, American Swiss, Angler and other breeds of global importance, play an important role in the program for breeding new highly productive dairy types and breeds in our country. The relevance of research carried out in this direction is also confirmed by the fact that the Ayrshire breed is generally recognized as the most selected for a number of economically useful and technological characteristics of the dairy breed. It is distinguished by abundant milk content in combination with high fat and milk content, almost excellent technological properties of the udder, high payment for feed by products, that is, it has the qualities that are required from animals in the conditions of a complex intensification of the industry. As a result of the study it was found that the positive effect of selection for milk yield and mass fat content (MDZh) in milk allows improving breed and productive qualities of cows through the selection of breeding stock and increase productive parameters for milk yield and its quality.
Magnetic Treatment of Sugar Beet to Reduce Weight Loss during Storage
Authors: Lysakov A A , Lubentsova E V , Apodgorny S , Ozhogova E V
Published: September 2021

Sugar beets are grown for sugar production. After harvesting, sugar beets are placed in closed storage for long-term storage. The main purpose of storage is to preserve sugar as much as possible in order to further ensure the profitability of processing beets for sugar. However, during storage of sugar beets, there is a rapid loss of moisture and weight. Beets, which have a weight loss of 13 … 17%, lose 5 times more sugar during storage than beets of good quality. One way to reduce the weight loss of sugar beet tubers is to use the magnetic field of a neodymium permanent magnet. Experimental studies on the treatment of sugar beet tubers with a magnetic field showed that the minimum weight loss of sugar beet tubers when treated with a negative magnetic field reached 15.3%, the minimum weight loss of sugar beet tubers when treated with a positive magnetic field reached 17.6%, and the weight loss of tubers sugar beet, not treated with a magnetic field, reached 25.6%. Thus, the nature of the influence of the magnetic field of a permanent neodymium magnet of positive and negative polarity on the weight loss of sugar beet tubers has been established.