bluuebunny/crossref_metadata_2025 huggingface dataset:
Temporal and spatial significance of volcanic particles in sand(stone): implications for provenance and palaeotectonic reconstructions
Authors: Critelli Salvatore , Criniti Sara , Ingersoll Raymond V. , Cavazza William
Published: July 2022

Volcanic particles have particular geodynamic significance. Despite abundant datasets on volcanic-derived sand(stone), the distinction between spatial and temporal distribution of volcanic particles within the sedimentary record is poorly documented. One of the most intricate tasks in optical analysis of volcaniclastic sand(stone) is the distinction of grains eroded from ancient volcanic rocks (palaeovolcanic, noncoeval grains) from grains generated by active volcanism during sedimentation (neovolcanic coeval grains). Petrologic methods are useful for deciphering temporal significance of volcanic particles in detail between palaeovolcanic and neovolcanic, and for active volcanism to decipher syneruptive v. posteruptive processes during deposition in sedimentary basins close to volcanoes. Sedimentary processes during syneruptive, intereruptive and posteruptive phases are well described in continental environments in terms of changing sedimentary facies, for example, the architecture (from body scale to stratigraphic scale), width/depth ratios of palaeochannels, palaeosols and composition of fluvial-channel deposits, whereas they are less documented in deep-marine environments. Examples of volcaniclastic sedimentation derived from both palaeovolcanic and neovolcanic sources are found in diverse geotectonic settings.
Quantized Sparse Training: A Unified Trainable Framework for Joint Pruning and Quantization in DNNs
Authors: Park Jun-Hyung , Kim Kang-Min , Lee Sangkeun
Published: July 2022

Deep neural networks typically have extensive parameters and computational operations. Pruning and quantization techniques have been widely used to reduce the complexity of deep models. Both techniques can be jointly used for realizing significantly higher compression ratios. However, separate optimization processes and difficulties in choosing the hyperparameters limit the application of both the techniques simultaneously. In this study, we propose a novel compression framework, termed as quantized sparse training, that prunes and quantizes networks jointly in a unified training process. We integrate pruning and quantization into a gradient-based optimization process based on the straight-through estimator. Quantized sparse training enables us to simultaneously train, prune, and quantize a network from scratch. The empirical results validate the superiority of the proposed methodology over the recent state-of-the-art baselines with respect to both the model size and accuracy. Specifically, quantized sparse training achieves a 135 KB model size in the case of VGG16, without any accuracy degradation, which is 40% of the model size feasible based on the state-of-the-art pruning and quantization approach.
On the use and misuse of cerebral hemodynamics terminology using transcranial Doppler ultrasound: a call for standardization
Authors: Skow Rachel J. , Brothers R. Matthew , Claassen Jurgen A. H. R. , Day Trevor A. , Rickards Caroline A. , Smirl Jonathan D. , Brassard Patrice
Published: July 2022

Cerebral hemodynamics, e.g., cerebral blood flow, can be measured and quantified using many different methods, with transcranial Doppler ultrasound (TCD) being one of the most commonly used approaches. In human physiology, the terminology used to describe metrics of cerebral hemodynamics are inconsistent and in some instances technically inaccurate; this is especially true when evaluating, reporting, and interpreting measures from TCD. Therefore, this perspective article presents recommended terminology when reporting cerebral hemodynamic data. We discuss the current use and misuse of the terminology in the context of using TCD to measure and quantify cerebral hemodynamics and present our rationale and consensus on the terminology that we recommend moving forward. For example, one recommendation is to discontinue the use of the term “cerebral blood flow velocity” in favor of “cerebral blood velocity” with precise indication of the vessel of interest. We also recommend clarity when differentiating between discrete cerebrovascular regulatory mechanisms, namely, cerebral autoregulation, neurovascular coupling, and cerebrovascular reactivity. This will be a useful guide for investigators in the field of cerebral hemodynamics research.
Identification of Sports Athletes’ High-Strength Sports Injuries Based on NMR
Authors: Zhou Wenyong , Chu Huan
Published: July 2022

In order to study the high-strength sports injury in sports, this paper proposes a method based on NMR to identify the high-strength sports injury of sports athletes. This method carries out a questionnaire survey and research on the athletes who are excellent in sports dance major from 2019 to 2021 in the Institute of Physical Education. The athletes’ age range is 18-25 years, and the training period of sports dance is 3-5 years. The results show that compared with other recognition methods, the recognition method based on NMR has higher accuracy and efficiency. The method of this study is helpful to improve the recognition efficiency and accuracy. Athletes are very easy to get injured during sports. In order to reduce the degree of injury of athletes, we should strictly follow the action standards in the training process to avoid serious injury.
Target Recognition, Localization, and Motion Control of Soccer Robot
Authors: Zhu Changsheng , Gong Min
Published: July 2022

The realization of target tracking includes many technologies, among which the most critical and core element is the target tracking algorithm. Based on this, this paper first uses an omnidirectional vision image enhancement algorithm to identify the target and then designs an adaptive target recognition algorithm based on SVM to identify the actual target. The results show that, in the case of different illuminance, the fluctuation range of the four evaluation indexes after image enhancement is smaller than that of the original image, indicating that the brightness distribution of the image after enhancement is more uniform, which eliminates interference factors for the subsequent image recognition and tracking. The difference of recognition rate between the two algorithms is small when the illumination value is medium. When the illumination value is high or low, the recognition rate of the adaptive algorithm is much higher than that of the threshold method.
Analysis of the Prevalence, Location, and Morphology of Maxillary Sinus Septa in a Northern Chinese Population by Cone Beam Computed Tomography
Authors: Wang Wenjuan , Jin Ling , Ge Huabing , Zhang Fengqiu
Published: July 2022

Purpose. The purpose of this study is to survey the prevalence and morphology of the maxillary sinus septum, which might increase the rate of maxillary sinus membrane perforation during maxillary sinus floor elevation surgery, among northern Chinese, and to further analyze the relationship between gender, age, edentulous type, and prevalence of maxillary sinus septa. Methods. The cross-sectional retrospective study was based on an analysis of Cone Beam Computed Tomography (CBCT) images of maxillary sinus which had been obtained from patients who visited radiology department of Beijing Stomatology Hospital of Capital Medical University (Beijing, China) during the period from January 2019 to December 2019. The data of demographic characteristic, prevalence, position, direction, and morphology of maxillary sinus septum were collected and further analyzed by SPSS version 25.0.1 and R version 3.5.1 software program. Results. 595 patients were included in this study, and 1190 maxillary sinuses were analyzed and the incidence rate of the sinus septum was 46.9%. 399 (33.5%) sinuses had one or more septa in 279 (46.9%) patients. In addition, maxillary sinus septa incidence showed no significant differences among gender, age, and edentulous type. The segment second molar had the highest incidence rate of septa. Conclusion. In this study, a higher incidence of the maxillary sinus septum was found in the northern Chinese, and its distribution varied with its position, morphology, and direction.
Network Pharmacology-Based Strategy to Investigate the Mechanisms of Cibotium barometz in Treating Osteoarthritis
Authors: Chen Guang-Yao , Wang Yi-Fei , Yu Xin-Bo , Liu Xiao-Yu , Chen Jia-Qi , Luo Jing , Tao Qing-Wen
Published: July 2022

Cibotium barometz is a representative tonifying kidney drug and is widely used for osteoarthritis (OA) in traditional Chinese medicine. However, its regulatory mechanisms in treating OA remain to be sufficiently investigated. The main chemical components of Cibotium barometz were screened through the TCMID database and the corresponding targets were acquired through SwissTargetPrediction. The OA-related targets were obtained from the OMIM, Genecards, Genebank, TTD, and DisGeNET databases. The prediction of key targets and pathways of Cibotium barometz in the treatment of OA was achieved by constructing a compounds-targets network and performing KEGG enrichment analysis. The OA model rats were established by the Hulth method and used to explore the protective effect of Cibotium barometz via cartilage pathological assessment. In vitro models of OA were built by the proinflammatory factor interleukin-1β (IL-1β) induced SW1353 cells and used to validate the mechanisms predicted by network pharmacology. Network pharmacology results suggested that the therapeutic effects of Cibotium barometz were closely related to matrix metalloproteinase (MMP)-1, 3, 13 and inflammation-related gene COX2, which are regulated by the NFκB pathway. In vivo experiments revealed that Cibotium barometz could effectively restrain cartilage from degeneration and inhibit the mRNA expression of MMP-1, MMP-3, MMP-13, and COX2 in cartilage. In vitro experiments indicated that Cibotium barometz water extract (CBWE) could significantly inhibit the expression of MMP-1, MMP-3, MMP-13, and PGE2 in IL-1β-induced SW1353 cells and markedly prevent the translocation of NFκB p65 from the cytoplasm to the nuclei and decrease its phosphorylation level. After small-interfering RNA (siRNA) was used to suppress the synthesis of NFκB p65 to block NFκB signaling pathway, the ability of CBWE to inhibit MMP-1, MMP-3, MMP-13, and PGE2 was greatly reduced. Cibotium barometz has a chondroprotective effect on OA by inhibiting the response to inflammation and substrate degradation, and the related mechanism is associated with the inhibition of the NFκB pathway.
Efficient Delay-Aware Task Scheduling for IoT Devices in Mobile Cloud Computing
Authors: Jin Chenghou , Xu Jiajie , Han Yusen , Hu Jintao , Chen Ying , Huang Jiwei
Published: July 2022

The development of Internet of Things (IoT) technology depends on technologies such as high-efficiency storage and high computing power. Mobile cloud computing (MCC) technology will be an important foundation for the development of IoT. The efficient scheduling of tasks in IoT devices in MCC environment is challenging. The requirements for task scheduling in MCC are becoming more and more complex. As the core problem in MCC, task scheduling aims to allocate tasks reasonably, achieve optimal scheduling strategies, and complete tasks effectively. In this paper, efficient delay-aware task scheduling algorithm (EDTSA) is proposed, with the optimization goal of minimizing task running time. The matching of tasks and virtual machines is modeled as a bipartite graph. The problem is divided into multiple subproblems to solve the optimal solution separately. The combined solution is used as the initial solution of the local search algorithm. The efficiency of the local search depends on the quality and nature of the initial solution. We can generate multiple initial solutions according to different division criteria. The initial solution is the combination of the optimal solutions of the subproblems, so the quality of the initial solution has been greatly improved and generating multiple initial solutions according to the division can reduce the probability of falling into the local optimal solution. This algorithm also divides the neighborhood to reduce unnecessary searches. Finally, we verify the efficiency and practicability of the algorithm through experiments.
Multi-Criteria Decision-Making Approach for Analyzing Competency Model of Technology Managers
Authors: Lin Chunbo , Liang Hanyuan , Su Taiyu , Tefera Minyechil Alehegn
Published: July 2022

The economies of all the countries are growing with the passage of time. In order to promote the businesses in the global markets, technology managers/technical brokers play a key role such as in the optimal allocation of scientific and technological resources. The industrialization of scientific and technological achievements is also possible due to optimal utilization of resources and a balance between exports and imports. The technology managers should be competent enough to bridge the gaps between the resource requirements and the availability of the resources required to run the businesses smoothly. This paper is using multi-criteria methods for analyzing the qualities in the technical managers which can assist the managers to run the businesses in an efficient manner to compete in the global markets. The interviews and questionnaire are used to collect the primary data. The opinion of experts is also considered. Then, SPSS 22.0 statistical analysis software is used to analyze the reliability and validity of the factors considered in the questionnaire. Then by using statistical techniques, a quantifiable competency model of technology managers is constructed. The multi-criteria AHP (analytical hierarchical process) method is used to compare the competency characteristic indexes of each level in pairs and quantitatively describe their importance of the criteria. It also assigns weights to judge the importance of each competency characteristic index. Since the evaluation of technical managers’ competency will be affected by various factors as mentioned in the paper, the fuzzy comprehensive evaluation method is also used to transform the evaluation dimension to accurately evaluate the competency of the technical manager which assists to judge the effectiveness of model evaluation. The proposed method provides theoretical and practical basis for the selection, evaluation, and cultivation of technical managers. It provides accuracy in results by 94% by adopting the statistical techniques.
Seismic Inversion Problem Using a Multioperator Whale Optimization Algorithm
Authors: Ni Rui , Liang Xiaodan
Published: July 2022

The whale optimization algorithm (WOA) is a metaheuristic algorithm based on swarm intelligence and it mimics the hunting behavior of whales. It has the imperfection of premature convergence into local optima. In order to overcome this disadvantage, a multioperator WOA (MOWOA) is proposed. Four main strategies are introduced to the MOWOA to heighten the search capacity of WOA. The strategies include nonlinear adaptive parameter design, an exploration mechanism of honey badger, Cauchy factor strategy, and greedy strategy. This paper tests the versatility of MOWOA with three different types of benchmark functions, and a kind of seismic inversion problem are trialed run. From the experimental results, the performance of MOWOA outperforms the compared algorithms in global optimization.
An Overview of Cable-Driven Parallel Robots: Workspace, Tension Distribution, and Cable Sagging
Authors: Tho Tuong Phuoc , Thinh Nguyen Truong
Published: July 2022

The researching, designing, calculating, and controlling cable-driven parallel robots (CDPRs) are being promoted in recent years. The researches focus on optimizing the design of CDPRs configuration, computing workspace, calculating cable tension distribution, designing the mechanical structure, and developing controller. However, due to the complexity of the structure and unidirectional characteristic of cable, many computational methods have been applied to solve the above problems. To facilitate the performance of theoretical studies on important issues in the design and control of the CDPRs, a summary of computational methods is needed for important issues related to the functionality and accuracy of CDPRs such as defining the workspace, distributing the cable tensions, and calculating the sagging of the cable. This paper summarizes published studies on CDPRs and focuses on classifying and analyzing methods used to calculate important issues in the process of calculating and designing CDPRs. The efficiency of these calculation methods is also analyzed and evaluated based on the mathematical theories of kinematics and dynamics of CDPRs. The content of this study is an effective reference for studies on important problems in the process of designing and implementing CDPRs, helping researchers shorten the time to review related topics.
Analysis of the Artistic Effect of Garden Plant Landscaping in Urban Greening
Authors: Tian Lin
Published: July 2022

At present, China is at an essential stage in the progress of social civilisation. At the same time, China's current economic level is developing rapidly and the level of urbanisation is also increasing. However, the uncontrolled development of urban space and excessive consumption of land resources have led to many urban ecological and environmental problems. As a result, there is an urgent need to improve the urban habitat. Plant landscaping is an important part of the urban environment. In addition, plant landscaping is also a crucial part of the visual arts and plays a key role in the shaping of urban spaces. In the context of the urban construction boom, people are increasingly demanding quality in the urban environment. Spatial scale, as a vital factor influencing the visual effect of planting, is gradually becoming a focus of landscape design. Urban greening based on plant landscape can not only improve the urban ecological environment and enhance people’s quality of life but also resolve the contradiction between the demand for urban green space and the continuous reduction of urban greening land. Therefore, plant landscaping is recognised as a key step towards global sustainable development. However, according to current research and application practice, the development of urban greenery is limited and hindered by the value of plant landscaping and its applications. In addition, no comprehensive theoretical system has yet been established at the plant scale. In other words, there are still problems of scale in plant landscaping, such as unreasonable density, disproportion, and unclear hierarchy. Therefore, this paper begins with the definition of plant spatial scale in the city and analyses plant spatial types and scale characteristics from multiple perspectives, so as to establish an overall knowledge of plant landscaping. After that, through a study of the current situation of plant landscaping in cities, a quantitative analysis of the visual scale of plant space in urban squares is carried out to address the issues of plant scale design in this research. The focus of the analysis is on the scale of plants in relation to related elements. Furthermore, this study explores the influence of visual aesthetic scale and psychological scale on planting based on the functional scale of plant elements. Finally, the above quantitative analyses are applied to derive some relative data criteria and to summarise the design strategies for the spatial scale of planting in the city. The findings of this study can provide some guiding suggestions and references for the future construction of urban greenery, thus promoting the orderly development of plant landscaping in cities.
[Retracted] The Optimization Strategy of College Students’ Ideological and Political Management under the Internet+ Environment
Authors: Zhou Ya
Published: July 2022

In order to better deal with the challenges brought by the changes of the external environment to the ideological and political work of college students and better solve the problems of dogma, lack of operability, and inability to adapt to the changes of the new situation and environment, this topic proposes a student management information system based on the artificial neural network. This method strengthens the construction of the student management system, deeply interprets the connotation and practical needs of ideological and political work in colleges and universities in the new environment under the background of the “Internet+” era, and is committed to further optimizing the strategy of student ideological and political work on the basis of following the principles of innovation, human nature, openness, and ecology of ideological and political work. The results show that the construction of a more scientific student teaching management information system can provide intelligent and digital technical support for the improvement of ideological and political work efficiency and teaching quality and promote the innovative development of ideological and political work in colleges and universities. Therefore, the ideological and political work in colleges and universities should gradually overcome preaching, build new methods to measure students’ achievements and ideological and political arms, actively occupy the dominant power of Internet discourse, and avoid the negative impact of the network by spreading positive energy.
Behavioral Analysis of EEG Signals in Loss-Gain Decision-Making Experiments
Authors: Shen Jiaquan , Liu Ningzhong , Li Deguang , Zhang Binbin
Published: July 2022

Extraction and analysis of the EEG (electroencephalograph) information features generated during behavioral decision-making can provide a better understanding of the state of mind. Previous studies have focused more on the brainwave features after behavioral decision-making. In fact, the EEG before decision-making is more worthy of our attention. In this study, we introduce a new index based on the reaction time of subjects before decision-making, called the Prestimulus Time (PT), which have important reference value for the study of cognitive function, neurological diseases, and other fields. In our experiments, we use a wearable EEG feature signal acquisition device and a systematic reward and punishment experiment to obtain the EEG features before and after behavioral decision-making. The experimental results show that the EEG generated after behavioral decision due to loss is more intense than that generated by gain in the medial frontal cortex (MFC). In addition, different characteristics of EEG signals are generated prior to behavioral decisions because people have different expectations of the outcome. It will produce more significant negative-polarity event-related potential (ERP) in the forebrain area when the humans are optimistic about the outcomes.
Comparison of Ventilator-Associated Pneumonia and Surgical Site Infection between Two Methods of Tracheostomy
Authors: Zhang Baozhi , Chen Chunyan
Published: July 2022

Objective. To compare the incidence of ventilator-associated pneumonia (VAP) and surgical site infection (SSI) between percutaneous dilatational tracheostomy (PDT) and surgical tracheostomy (ST). Methods. Data on 487 patients undergoing tracheostomy between 1st January 2014 and 30th September 2020 were reviewed. Patients were divided according to the surgical techniques. Clinical characteristics and postoperative care were compared to explore the risk factors for SSI and VAP. All tracheostomies were performed by intensivists who had completed at least ten tracheostomies. ST was performed using standard techniques. PDT was performed according to a modification technique described by Ciaglia. All procedures were performed at the bedside in the ICU. Results. Of all, 344 patients (70.6%) were men and 143 (29.4%) were women, and the mean age was 56 years (standard derivation [SD] 12 years). Two hundred and sixty-six patients (54.6%) received PDT, and 221 (45.4%) received SY. Patients in the PDT group had a significantly lower rate of SSI (3.4% vs. 8.5%,

P
=
0.01

) compared with the ST group. Multivariate analysis revealed that comorbidities (

P
=
0.003

), surgical type (

P
=
0.01

), and cluster nursing (

P
<
0.001

) were independent risk factors for SSI; age (

P
=
0.005

), comorbidities (

P
<
0.001

), smoking (

P
=
0.008

), and cluster nursing (

P
=
0.01

) were independent risk factors for VAP. Conclusion. PDT significantly reduces the risk of SSI. Proper care should be administrated in patients with one or more risk factors of SSI or VAP to prevent the occurrence of complications.
Determinants of Adoption of Improved Dairy Technologies: The Case of Offa Woreda, Wolaita Zone, Southern Ethiopia
Authors: Zemarku Zekarias , Senapathy Marisennayya , Bojago Elias
Published: July 2022

One of the agricultural activities of rural farmers is dairy farming. Furthermore, by providing income, it has the potential to make farm households rich. The objective of this study was to analyze the general factors that influence adoption decisions, as well as the status of adoption of dairy technology in the Offa district, Wolaita zone, southern Ethiopia. The study area has fundamental factors influencing the adoption of dairy technologies which were unknown. This research was started to fill a knowledge gap for responsible bodies. Four kebeles were selected randomly for the study. 150 sample households (63 adopters and 87 nonadopters) were chosen using the SRS (systematic random sampling) method. The interview schedule was used to collect primary data from these households. Secondary data were gathered from a variety of sources, including reports, research findings, documents, and publications. Both quantitative and qualitative data were analyzed by using descriptive and econometric analyzes by SPSS version 21. Focus group discussions and key informant interviews were also used to collect qualitative data. A binary logistic regression model was used to examine the factors that influence the adoption of dairy technologies. The results of the binary logistic regression model revealed that both dairy technology participants and nonparticipant households experienced a combination of personal, demographic, economic, and institutional factors that hindered adoption. Respondent age, access to credit services, size of household landholding, frequency of the extension contact, involvement of outside income, livestock ownership, and distance from the nearest market were all significant negative contributing factors. On the other hand, farm income and dairy farming experience were positively significant variables in the model. Technical assistance to improve farm productivity and income, experience sharing and field visit programs to the fields of early experienced dairy farmers, improvement of farmland usage, improvement of road infrastructure in the study area, provision of appropriate and modernized training and extension services, and so on are among the recommendations.
Experimental Investigation on the Effects of Coffee Husk Ash as Partial Replacement of Cement on Concrete Properties
Authors: Gedefaw Asmamaw , Worku Yifru Begashaw , Endale Solomon Asrat , Habtegebreal Betelhem Tilahun , Yehualaw Mitiku Damtie
Published: July 2022

The production of cement results in the depletion of natural resources and consumption of huge energy and CO2 emissions to the environment that cause global warming and climate change. To alleviate the problem, there is a growing interest of researchers to find an alternative material to partially cement by industrial and agricultural wastes. This research was therefore aimed to examine the potential of using coffee husk ash (CHA) as partial replacement for ordinary Portland cement (OPC) in C-25 concrete production. Concrete mixtures were prepared by partially replacing cement with CHA in different proportions (0%, 5%, 10%, and 20%) by weight with a constant w/c of 0.5. The consistency, setting time, workability, compressive strength, water absorption, sulphate attack, Fourier transform infrared (FTIR), and thermo gravimetric (TGA) tests were conducted on concrete samples. The test results revealed that the workability of mixtures showed a decreasing trend with an increase in the share of the CHA content in which the measured slump flow values ranged between 15 and 35 mm. Contrarily, the setting time of concrete mixtures showed an increasing trend with an increase in CHA content. The initial and final setting times were in the range of 67–126 minutes and 310–524 minutes, respectively, which is in the range of the standards. The compressive strength of concrete decreased with an increase in the share of the CHA, in which the results were measured in the range of 35.1–22.7 MPa for the 28th day sample with 5% and 20% of CHA, respectively. However, it increases as the curing days increase, whereas the water absorption of the concrete increases as the CHA increases but decreases as the curing days increase due to the porous nature of the CHA. From the study microstructure of concrete using Fourier transform infrared spectroscopy and thermogravimetric analysis, differential thermal analysis results show that the C-S-H gel would be from 950–1100 cm−1 wavenumber and at 500oC, and the CHA sample was decomposed and mass loss was observed at 500oC. In general, it was also observed that, from the compressive strength, the concrete satisfies its design strength up to 10% replacement level without compromising the performance of concrete.
Safe Distance of Virus Quantitative Analysis and Simulation of the Trajectory of Pathogen-Containing Droplets in the Air Respiratory Airways
Authors: Miao Hanwen Alvin
Published: July 2022

Droplets of mucosalivary ejecta emitted by sneezing or coughing are a major carrier of numerous types of bacterial and viral diseases. This study develops a numerical model to estimate the spread distance for inhalable droplets (1–50 μm) in the air, the inhalability of the particles, and the trajectory as well as velocity of these pathogen-containing droplets in human respiratory airways. Moreover, particularly for droplets with diameters of 1 μm, 5 μm, 10 μm, and 50 μm, specific comparisons between their inhalability and transmission velocities are made. Data extracted from previous experiments proceeded by other researchers discussing the visualization of sneeze ejecta and deposition features of inhaled drops were used to obtain parameters to fit the model prediction of this work. Currently, research on similar topics was mostly based on either experiments or theoretical calculations only on one specific clan of pathogen, while the novel contribution of this paper is the combination and comparison of these two distinct methodologies that can be applied to solve a general practical problem aiming to all types of viruses by considering the pathogen-containing droplets as a whole entity.
Toxicological Evaluation and In Silico Identification of Acetylcholinesterase Inhibitors in a Commercial Polyherbal Formulation (KWAPF01)
Authors: Aladodo A. Raliat , Ibrahim Ibrahim O. , Sabiu Saheed
Published: July 2022

This study investigated the toxicological implications of a commercial polyherbal formulation, KWAPF01. Twenty-four Wistar rats were randomized into six groups of four animals per group. The animals in Group 1 were administered placebo and designated as control, while the rats in Groups 2 to 6 were administered 1000, 1500, 2000, 2500, and 3000 mg/kg bodyweight single oral dose of KWAPF01, respectively, and subsequently monitored for gross morphological and behavioural changes for 72 h. Piloerection, reduced motility, and tremor were observed in experimental groups, and the median lethal dose (LD50) of the extract was 2225.94 mg/kg bodyweight. The 11 compounds identified through HPLC analysis of the extract were docked against acetylcholinesterase (AChE), and the docking scores ranged from −5.3 to −10.8 kcal/mol, with catechol (−5.3 kcal/mol) and berberine (−10.8 kcal/mol) having the highest and lowest binding energies, respectively. Judging by the results, it could be inferred that some of the constituents of KWAPF01 have a direct impact on the nervous system and this is possibly elicited via the cholinergic system as it contains a nicotinic acetylcholine receptors agonist and potential inhibitors of AChE. Therefore, the use of KWAPF01 needs to be cautiously guided.
High-Intensity Ultrasound-Assisted Extraction of Pectin from Mango Wastes at Different Maturity
Authors: Torres-Gallo Ramiro , Bayuelo-Bonilla Sulibeth , Carpio-Ortiz Luz , Barreto-Rodríguez Genisberto , Tirado Diego F.
Published: July 2022

Valorisation of food processing by-products is a welcome and developing area. The mango processing industry produces 40% to 60% of the fruit as solid waste, in which components of industrial interest, such as pectin, are lost. This study reports on energy-efficient high-intensity ultrasound-assisted extraction (HIUAE) to extract pectin from mango peels. The analysis considered the ripening stage of the fruit (0, 2, and 4), HIUAE frequency (37 kHz and 80 kHz), and extraction time (20 min, 25 min, and 30 min). Extractions of pectin from mango peels with HIUAE have been fairly studied. However, this work differs from those studies in including mango maturity grade as a factor. Pectin extraction yields ranged from 13% to 30%, with no influence (

p
>
0.05

) of time, and the highest yields were obtained at the lowest maturity stage (0) and lowest frequency (37 kHz). This latest condition (37 kHz) also yielded pectin with the highest gel strength, purity, and quality. This work demonstrated that the mango maturity stage influenced pectin extraction yield. Ultrasound-assisted extraction of pectin from mango peels could be an efficient approach toward waste valorisation and extraction of pectin with high yield and good quality attributes for the food industry.
Influencing Factors and Coping Strategies of Hospitalization in Children with Leukemia Complicated with Pneumonia
Authors: Xiang Rongmei , Yi Jiang
Published: July 2022

Objective. To investigate the influencing factors of pneumonia when pediatric leukemia patients are hospitalized and propose coping strategies. Methods. A retrospective study and analysis of the inpatient medical records of 183 children with leukemia in our hospital from August 2017 to August 2020. A total of 93 cases were in the case group of children with pneumonia, and the rest were 90 cases in the control group. Case data from two groups of children were compared, and the monofactor analysis of pneumonia occurred. The

P
<
0.05

was selected for its multivariate logistic regression analysis, and its coping strategy was proposed. Results. After multivariate logistic retrospective analysis, it was found that the main influencing factors were neutrophils, white blood cells, vitamin D, and cellular immunity (

P
<
0.05

). A review of the two sets of pathological data found that high doses of cytarabine reduced the incidence of pneumonia in children with leukemia (

P
<
0.05

). Conclusion. A timely understanding of the influencing factors of pediatric diabetes mellitus and pneumonia and the early application of cytarabine can reduce the incidence of pneumonia during the child’s hospitalization.
Fast and Intelligent Irrigation System Based on WSN
Authors: Oussama G. , Rami A. , Tarek F. , Alanazi Ahmed S. , Abid M.
Published: July 2022

In the agricultural industry, wireless sensor networks (WSNs) can be an important tool to promote economic growth. Using network devices in agriculture has the potential to enhance the production process. One of the key challenges WSN faces is energy efficiency. A model based on the water pipeline method is proposed in order to efficiently utilize sensor nodes in agricultural production and water distribution. A water pipeline serves as an important structure for transporting potable water across a distance for consumption or irrigation. In contrast, the biggest transportation problems of water pipelines are leaks. So, water resources may be lost as a result. These pipes need real-time monitoring to prevent such problems. The wireless sensor network technique, however, is considered one of the best solutions available today for monitoring water pipelines. A detailed analysis of agriculture is provided by the model. Aspects of WSN are discussed and their agricultural use is expounded. Moreover, this paper describes the various types of applicability of existing sensor networks in the field of agriculture, along with some technical perspectives. To achieve the best power consumption and communication for the two types of range, ZigBee wireless protocols are utilized. As such, high-performance information that provides a platform for WSNs to better support agricultural production is also included in our proposed model in order to address the shortcomings of existing WSNs regarding energy efficiency. This paper presents the improvements of the proposed solution compared to other techniques in the context of energy conservation in wireless sensor networks and in the monitoring water-saving process.
Effects of Acupuncture on Cortical Activation in Patients with Disorders of Consciousness: A Functional Near-Infrared Spectroscopy Study
Authors: Wen Xin , Liu Zicai , Shao Yuchun , Peng Yang , Liu Huiyu , Wang Minghong , Chen Junbin
Published: July 2022

Background. Disorder of consciousness (DoC) is a clinical condition caused by severe brain damage. Some studies have reported that acupuncture, a traditional Chinese treatment, could facilitate the recovery of the patient’s consciousness. The therapeutic effects of acupuncture may be due to its modulation of facilitating cortex (PFC) activity, but it has not been greatly demonstrated. Objectives. We intended to observe the effects of acupuncture on prefrontal cortical activity, explore the potential correlation between cortical activation and the severity of DoC, and analyze the functional brain network connectivity to provide a theoretical basis for its application in clinical practice. Methods. Participants diagnosed with DoC were included in the study. Before the intervention, we assessed the patient’s state of consciousness using relevant scales, such as the Glasgow coma scale (GCS) and the coma recovery scale-revised (CRS-R). All patients received acupuncture manipulation with the functional near-infrared spectroscopy (fNIRS) system monitored. Result. A total of 16 subjects participated in our study. We observed that the concentration of oxygenated hemoglobin (HbO) in the PFC was increased during the acupuncture manipulation and declined during the resting state. Then, the connection strength of the left cerebral cortex was generally higher than that of the right. Finally, we observed only a weak difference in hemodynamic responses of PFC between the vegetative state (VS) and minimally conscious state (MCS) groups. However, the difference was not statistically significant. Conclusion. Our results indicated that acupuncture can increase the concentration of HbO in the PFC and strengthen the connection strength of the left cerebral cortex. However, our present study did not find a significant correlation between the cortical hemodynamic response and the severity of DoC.
Research on Online Virtual Energy-Saving and Environment-Friendly Building Design and Implementation Based on VRML
Authors: Lai ZhengWen , Zeng QingLiang , Zhou Shiyuan
Published: July 2022

In order to change the status quo of lacking holistic and intuitive research on building energy efficiency in China, an online virtual energy-saving and environment-friendly building system based on VRML was proposed. The two subsystems of virtual simulation technology, “virtual reality” and “energy consumption simulation,” were integrated and applied to the design research of building energy efficiency. On the basis of inheriting the advantages of the traditional way, the independent application mode of the two was changed. The application analysis was carried out using a real energy-saving demonstration project as the research object. The experimental results showed that the energy-saving rate of the enclosure structure of the three buildings was 35.742%, 30.408%, and 35.696%, respectively. It was concluded that the system provided a more systematic and intuitive method to the design and research of building energy efficiency.
PPP Financing Model in the Infrastructure Construction of the Park Integrating Artificial Intelligence Technology
Authors: Wang Xiufeng , Cui Xiaoyan
Published: July 2022

The objective is to study the application of the Public-Private-Partnership (PPP) financing model in the infrastructure construction of the park. By analyzing the operation model of the PPP financing model, combined with the Artificial Intelligence (AI) technology, the theory mechanism that digital infrastructure construction and Internet use affect the quality of employment is proposed. Based on the selection theory of the PPP model for infrastructure construction projects in industrial parks, the application of the PPP financing model in infrastructure construction of industrial parks is discussed in specific cases. According to the actual situation of the case, the combination of the PPP financing model and government direct investment is proposed, and the predicted income results are given. The results manifest that the total score of the qualitative analysis of the value for money (VFM) of the project of the proposed financing model reaches 85.36 points, greater than 60 points. It indicates that the project has passed the qualitative analysis of VFM, and the profit of the project meets expectations. Among them, the after-tax (AT) internal rate of return of project investment reached 4.3%, and the financial internal rate of return of capital amount reached 4.23% AT, exceeding expectations. It illustrates that the designed PPP financing model meets the requirements. In the infrastructure construction of the park, the combination of digital technology and the PPP financing model can provide a more reasonable financing plan, which is feasible for the infrastructure construction of the park.
Decentralized Vehicular Mobility Management Study for 5G Identifier/Locator Split Networks
Authors: Hong Gaofeng , Yang Bin , Su Wei , Wen Qili , Hou Xindi , Li Haoru
Published: July 2022

The identifier/locator split (ILS) architectures are highly promising to reduce the signaling latency of frequent handovers in fifth generation (5G) networks, while decentralized vehicular mobility management holds greater potential than the traditional centralized management to enhance the critical performance of highly dynamic and dense cell networks. By carefully exploiting ILS, dual connectivity, and multiaccess edge computing (MEC) concepts, this paper proposes a decentralized vehicular mobility management mechanism in the network with dense 5G Non-Standalone deployment. Under such a mechanism, we design an ILS-based local anchor handover management architecture to reduce signaling costs and handover latency. Specifically, we propose a quality of service- (QoS-) based handover decision algorithm using a long short-term memory- (LSTM-) based trajectory prediction method to obtain the cell sojourn time of connected vehicles (CVs) in predefined QoS coverage areas. Combining a built-in dynamic handover trigger condition, this algorithm can ensure a flexible load balance as well as low handover times. Extensive simulation results are presented to verify the effectiveness of the proposed mechanism in improving network performance.
Teaching Quality of College Students’ Mental Health Based on Mathematical Programming Algorithm
Authors: Cai Bin , Wang Dongsheng
Published: July 2022

During the evolution of the twenty-first century, the increase in people’s material life level has also brought an increase in mental stress. For college students, not only need to bear heavy academic pressure, but also face the market competition after entering the society. Therefore, the psychological fitness instruction for undergraduate students has become an inseparable part of college education. However, in the current stage of mental health education, the quality of teaching is often difficult to guarantee. For the purpose of promoting the in-depth implementation of mental health education in colleges and universities and improving teaching effectiveness, one needs to analyze the quality of teaching in great details and understand the factors affecting the quality of teaching. In this paper, the mathematical programming algorithm is used to analyze the quality of college students’ Psychological Wellness Instruction. It deeply studies the development status of psychological wellness training and the basic composition and algorithm principle of mathematical programming algorithm. It integrates it into the practice of teaching quality analysis on the basis of linear regression algorithm theory. The experimental results show that the highest confidence interval of teachers’ teaching organization, cognitive level, and students’ participation level in the mental health course has reached more than 80.00%. This shows the importance of these three factors to the improvement of teaching quality. In order to enhance the quality of college students’ psychological wellness training, it is necessary to innovate the form of classroom organization and the degree of interaction between students and the classroom.
Classification, Processing Procedures, and Market Demand of Chinese Biscuits and the Breeding of Special Wheat for Biscuit Making
Authors: Hu Xin , Hu Lejia , Zheng Jing , Rong Junkang
Published: July 2022

With the improvement of living standards, consumers’ demand for wheat food is gradually diversified. Biscuit, as a kind of convenience food, becomes a consumer’s leisure snack due to its characteristics such as low processing cost, easy-to-carry and convenient-to-eat traits, long shelf life, diverse varieties, and rich tastes, which have attracted more and more people. Biscuits are composed of four main ingredients, which are flour, fat/oil, sugar, and water, whereas several secondary ingredients also are important sources of high molecular carbohydrates, plant proteins, vitamins, and minerals for human beings. In this study, we systematically summarized the related research of biscuits, including the main types of China’s biscuits, the market demands, and statistics of wheat planting, production, and import in recent ten years, as well as the research of soft wheat breeding for biscuit. The flour consumption of biscuit industry has been maintained at more than 4 million tons, accounting for more than 30% of the flour consumption in food industry. The planting area of wheat in China has stabilized around 22.8 million hectares in 2010–2020, while the yield of wheat has increased 18.0% (20.86 million t) due to the increase of yield per unit of wheat. China’s total annual pastry import bill increased 5 times and the gap between import and export bill of pastry has been increased more than 7 times from 2010 to 2020, suggesting the strong demand of the national pastry market. This research also provides a direction for the future breeding of special soft wheat for biscuits in China.