bluuebunny/crossref_metadata_2025 huggingface dataset:
First estimates of diffuse gastric cancer risks for carriers ofCTNNA1germline pathogenic variants
Authors: Coudert Marie , Drouet Youenn , Delhomelle Hélène , Svrcek Magali , Benusiglio Patrick R , Coulet Florence , Clark Dana Farengo , Katona Bryson W , van Hest Liselotte P , van der Kolk Lizet E , Cats Annemieke , van Dieren Jolanda M , Nehoray Bita , Slavin Thomas , Spier Isabel , Hüneburg Robert , Lobo Silvana , Oliveira Carla , Boussemart Lise , Masson Laure , Chiesa Jean , Schwartz Mathias , Buecher Bruno , Golmard Lisa , Bouvier Anne-Marie , Bonadona Valérie , Stoppa-lyonnet Dominique , Lasset Christine , Colas Chrystelle
Published: August 2022

Background

Pathogenic variants (PV) ofCTNNA1are found in families fulfilling criteria for hereditary diffuse gastric cancer (HDGC) but no risk estimates were available until now. The aim of this study is to evaluate diffuse gastric cancer (DGC) risks for carriers of germlineCTNNA1PV.

Methods

Data from published CTNNA1 families were updated and new families were identified through international collaborations. The cumulative risk of DGC by age for PV carriers was estimated with the genotype restricted likelihood (GRL) method, taking into account non-genotyped individuals and conditioning on all observed phenotypes and genotypes of the index case to obtain unbiased estimates. A non-parametric (NP) and the Weibull functions were used to model the shape of penetrance function with the GRL. Kaplan-Meier incidence curve and standardised incidence ratios were also computed. A ‘leave-one-out’ strategy was used to evaluate estimate uncertainty.

Results

Thirteen families with 46 carriers of PV were included. The cumulative risks of DGC at 80 years for carriers ofCTNNA1PV are 49% and 57%, respectively with the Weibull GRL and NP GRL methods. Risk ratios to population incidence reach particularly high values at early ages and decrease with age. At 40 years, they are equal to 65 and 833, respectively with the Weibull GRL and NP GRL.

Conclusion

This is the largest series ofCTNNA1families that provides the first risk estimates of GC. These data will help to improve management and surveillance for these patients and support inclusion ofCTNNA1in germline testing panels.
A busy time at the beach: multiple examples of gregarious dinosaur behaviour inferred from a set of trackways from the Late Cretaceous of Alberta, Canada
Authors: Henderson Donald M. , Borkovic Benjamin , Sanchez Joseph , Kowalchuk Amy L.
Published: August 2022

A diverse collection of dinosaur tracks and trackways preserved on a single bedding plane record activities of many animals over a very short time, possibly just a few days or less. The assemblage is exposed on a detached slab of siltstone from the Campanian–Maastrichtian St. Mary River Formation in southwestern Alberta, Canada. Members of four different groups of dinosaurs are identified as the makers of either isolated tracks, or trackways of varying lengths, and include inferred hatchling tyrannosaurids, medium and large ornithomimids, small and medium-sized ornithopods, and a small hadrosaurid. All but one of the seven trackways attributed to hatchling tyrannosaurids occur as codirectional, equally spaced pairs, but one pair walked in the opposite direction, albeit parallel, to the other two. The pair of ornithomimid trackways also appears to represent two animals walking at the same speed, in the same direction, and turning together. The trackway attributed to a medium-sized biped, possibly Parksosaurus warreni, is the first evidence for the presence of these dinosaurs in the environment recorded by the St. Mary River Formation.
Endothelin-1 alters BMP signaling to promote proliferation of pulmonary artery smooth muscle cells
Authors: Maruyama Hidekazu , Sakai Satoshi , Ieda Masaki
Published: August 2022

Pulmonary arterial hypertension (PAH) is characterized by abnormal outgrowth of pulmonary artery smooth muscle cells (PASMCs) of the media. Abundant expression of endothelin-1 (ET-1) and activated p38 mitogen-activated protein kinase (p38MAPK) has been observed in PAH patients. p38MAPK has been implicated in cell proliferation. An unspecified disturbance in bone morphogenetic protein (BMP) signaling may be involved in the development of PAH. Type I receptors (BMPR1A and BMPR1B) and type II receptor (BMPR2) transduce signals via two distinct pathways, i.e., canonical and non-canonical pathways, activating Smad1/5/8 and p38MAPK, respectively. BMPR1B expression was previously reported to be enhanced in the PASMCs of patients with idiopathic PAH. BMP15 binds specifically to BMPR1B. We assessed the effects of ET-1 on BMP receptor expression and cell proliferation. BMP2 increased BMPR1B expression in human PASMCs after pretreatment with ET-1 in vitro. Although BMP2 alone did not affect PASMC proliferation, BMP2 treatment after ET-1 pretreatment significantly accelerated PASMC proliferation. PH-797804, a selective p38MAPK inhibitor, abrogated this proliferation. Similarly, after ET-1 pretreatment, BMP15 significantly accelerated the proliferation of PASMCs, whereas stimulation with BMP15 alone did not. In conclusion, in PASMCs, ET-1 exposure under pathological conditions alters BMP signaling to activate p38MAPK, resulting in cell proliferation.
Reconfigurable Architecture for DNA Diffusion Technique-Based Medical Image Encryption
Authors: Devipriya M. , Brindha M.
Published: August 2022

The aim of this paper is to develop and test the features of reconfigurable architecture for its suitability for a secured medical image encryption. The image security has been ensured using three-level zigzag confusion, bit-level confusion, self-invertible matrix and DNA diffusion. The zigzag pixel-level and circular shift-based bit-level confusion offer a good scrambling to overcome the correlation among the pixels whereas the self-invertible matrix is used to have a better substitution effect. The DNA operations are performed to get new random-valued sequence for diffusion thereby the encryption process has been designed to get good protection with simple and effective coding. The concept of secured medical image encryption has been designed using verilog HDL and implemented using field programmable gate array (FPGA) with an intention to create a standalone embedded hardware for encryption. The analysis of the encryption includes correlation coefficient, entropy, Chi-square analysis, NPCR and UACI and so on, which gives a better result and conveysto us that it can resist the statistical and differential attacks. The synthesis report of the embedded hardware has been presented to understand the utilization of the FPGA.
A Deep Learning-Based Robust Automatic Modulation Classification Scheme for Next-Generation Networks
Authors: Kumaravelu Vinoth Babu , Gudla Vishnu Vardhan , Murugadass Arthi , Jadhav Hindavi , Prakasam P. , Imoize Agbotiname Lucky
Published: August 2022

Due to stochastic wireless environment, the process of modulation classification has become a challenging task. Because of its powerful feature extraction ability and promising performance over the conventional schemes, deep learning (DL) models are employed to automatic modulation classification (AMC) problems. Most of the conventional models proposed are tested for the limited set of modulation schemes transmitted over additive white Gaussian noise (AWGN) channels without considering the effect of multipath fading and Doppler shift. The next-generation networks use adaptive and higher-order quadrature amplitude modulation (QAM) schemes for higher spectral efficiency. The classification accuracy of conventional DL-based AMC schemes drastically reduces, when different order QAM modulation schemes are accommodated. In this work, different scaling factors are selected for the generation of [Formula: see text]-QAM frames. The combination of scaling factors, which maximize the classification accuracy is chosen. A convolutional neural network (CNN) with six stages is employed for AMC. The simulation results show that the classification accuracy of proposed scheme is higher than the conventional DL-based schemes under various signal-to-noise ratio (SNR) conditions. The proposed scheme shows at least 4% improvement in classification accuracy over the other DL-based schemes.
Bifurcations and Bistability of an Age-Structured Viral Infection Model with a Nonmonotonic Immune Response
Authors: Wang Shaoli , Wang Tengfei , Chen Yuming
Published: August 2022

Recent studies have demonstrated that immune impairment is an essential factor in viral infection for disease development and treatment. In this paper, we formulate an age-structured viral infection model with a nonmonotonic immune response and perform dynamical analysis to explore the effects of both immune impairment and virus control. The basic infection reproduction number is derived for a general viral production rate, which determines the global stability of the infection-free equilibrium. For the immune intensity, we get two important thresholds, the post-treatment control threshold and the elite control threshold. The interval between the two thresholds is a bistable interval, where there are two immune-present infected equilibria. When the immune intensity is greater than the elite control threshold, only one immune-present infected equilibrium exists and it is stable. By assuming the death rate and virus production rate of infected cells to be constants, with the immune intensity as a bifurcation parameter, the system exhibits saddle-node bifurcation, transcritical bifurcation, and backward/forward bifurcation.
Limit Cycles in Discontinuous Piecewise Linear Planar Hamiltonian Systems Without Equilibrium Points
Authors: Li Zhengkang , Liu Xingbo
Published: August 2022

In this paper, we study the limit cycles in the discontinuous piecewise linear planar systems separated by a nonregular line and formed by linear Hamiltonian vector fields without equilibria. Motivated by [Llibre & Teixeira, 2017], where an open problem was posed: Can piecewise linear differential systems without equilibria produce limit cycles? We prove that such systems have at most two limit cycles, and the limit cycles must intersect the nonregular separation line in two or four points. More precisely, the exact upper bound of crossing limit cycles is two, and this upper bound can indeed be reached: either both intersect the separation line at two points or one intersects the separation line at two points and the other one at four points. Based on Poincaré map, the stability of various limit cycles is also proved. In addition, we give some concrete examples to illustrate our main results.
Spatiotemporal Pattern Formation in a Discrete Toxic-Phytoplankton–Zooplankton Model with Cross-Diffusion and Weak Allee Effect
Authors: Zhang Feifan , Tian Hao , Zhao Hongfan , Zhang Xinran , Shi Qiyu
Published: August 2022

Phytoplankton patterns have been observed widely in aquatic systems. Although pattern formation has been investigated based on many PDEs, discrete models on aquatic systems can provide more complex dynamics. A discrete toxic-phytoplankton–zooplankton model is studied in this paper, with the consideration of Allee effect and cross-diffusion. Focusing on Allee effect coefficient, flip and Neimark–Sacker bifurcation analyses are carried out. And focusing on cross-diffusion coefficient, Turing bifurcation analyses are carried out. Parameter conditions and bifurcation diagram of these bifurcations are obtained correspondingly. Numerical simulations are then performed which are consistent with results of theoretical analysis. Irregular patterns can be formed by flip bifurcation. Spirals can be formed by Neimark–Sacker bifurcation. Spots and stripes can be formed by Turing bifurcation. When Turing and flip, or Turing and Neimark–Sacker bifurcations both occur, special patterns can be obtained.
Noise-Induced Multirhythmicity, Bursting, and Order–Chaos Transitions in the 3D Goldbeter System
Authors: Ryashko Lev
Published: August 2022

Motivated by an attractive problem of elucidating the causes for the occurrence of complex oscillatory regimes in chemical reactions, we study the constructive role of noise in a three-dimensional enzymatic “substrate-two products” model. Stochastic effects are investigated in the parameter zone of birhythmicity where regular oscillatory attractors coexist with chaotic ones. Chaos–order transformations caused by stochastic transitions between these attractors are studied parametrically using the Lyapunov exponents. A special form of stochastic excitement of large-amplitude bursts consisting of the high-frequency spikes is revealed and investigated by statistical analysis.
Twenty-Six Crossing Limit Cycles Around One Singular Point in a Cubic Switching System
Authors: Li Jie , Tian Yun , Liu Yaru
Published: August 2022

In this paper, we obtain a lower bound for the maximum number of crossing limit cycles for cubic planar switching systems with two regions separated by a straight line. By pseudo Hopf bifurcation and [Formula: see text]-order Lyapunov constants, we prove that there exist cubic near-integrable switching systems with at least 26 small-amplitude limit cycles bifurcating from an elementary center after suitable perturbations. To the best of our knowledge, this is the best lower bound so far for the cubic class by using a first order analysis.
A NOVEL COMPUTATIONAL APPROACH FOR FRACTAL NONLINEAR POCHHAMMER–CHREE MODEL
Authors: LIU JUAN
Published: August 2022

The purpose of this paper is to establish a novel algorithm to find the fractal solitary wave solution for fractal nonlinear Pochhammer–Chree model based on fractal variational theory, which is called variational transform method (VTM). The numerical examples are given to reveal the effectiveness and simplicity of the proposed method. Finally, some physical properties of the obtained fractal traveling wave solutions are illustrated by some graphs. The novel method sheds a new light on the fractal soliton theory.
Electrochemical Sensor for Meropenem Therapeutic Monitoring in Human Plasma Based on Carbon Nanotubes Modified Basal Pyrolytic Graphite Electrode
Authors: Atta Madonna Y. , Hegazy Maha A. , Mahmoud Amr M. , Ghoniem Nermine S.
Published: August 2022

Sensitive, precise, and fast differential pulse voltammetric (DPV) method has been developed for determination of meropenem (MER) in pure form, pharmaceutical dosage form, and human plasma. The fabricated sensors are based on basal-plane pyrolytic graphite electrode (BPPGE) substrates that was modified by coating the surface with carbon nanotubes. The modified electrode showed detectable enhancement of the anodic peak current of meropenem from 25.8 to 35.7 μA. Effect of both pH and scan rate on peak current and potential were studied, optimum conditions were found to be at pH = 3.0 and scan rate of 100 mV.s−1. A linear response was obtained over the concentration range of 3.0 × 10−7 to 7.0 × 10−5 M MER in aqueous buffer solution. The suggested sensor is highly sensitive, has short response time, capable of MER detection as low concentration as 1.5 × 10−6 M in human plasma. The proposed sensors shows a great potential towards future fabrication of a point-of-care device to monitor MER level in patients’ plasma to ensure drug safety and efficacy for patients in intensive care unit.
Discussion and Application of Blockchain Technology in Information Management of Internet of Things in Smart Lab
Authors: Zhong Jian , Chen Hang , Zhang Qianyun , He Weiying
Published: August 2022

In today’s rapid development of higher education, the reform of higher applied undergraduate institutions and higher education has become an effective way to improve the quality of higher education personnel training and improved the quality of teaching. With the continuous expansion of the scale of university laboratories, the number of managers is also increasing, but the management of laboratories is still in the exploratory stage. The current laboratory information management system of Internet of Things has high degree of data heterogeneity, poor data interoperability, and difficult guarantee of data privacy, all of which lead to the difficulty in mining the data value of Internet of Things. The decentralized and zero-trust architecture of blockchain subverted the traditional centralized system architecture and has been applied in many aspects. Blockchain technology was a good addition to IOT to improve the privacy security, versatility, and reliability of the network. This thesis developed an IOT information management system for smart labs based on blockchain technology and the Internet of Things. The data processing efficiency, accuracy, and system throughput are compared with the original IOT laboratory information management system. The results showed that compared with the current laboratory IOT information management system, this system had higher speed, higher efficiency, and better performance in processing the information and data.
An Efficient Deep Learning Model with Interrelated Tagging Prototype with Segmentation for Telugu Optical Character Recognition
Authors: Dhanikonda Srinivasa Rao , Sowjanya Ponnuru , Ramanaiah M. Laxmidevi , Joshi Rahul , Krishna Mohan B. H. , Dhabliya Dharmesh , Raja N. Kannaiya
Published: August 2022

More than 66 million people in India speak Telugu, a language that dates back thousands of years and is widely spoken in South India. There has not been much progress reported on the advancement of Telugu text Optical Character Recognition (OCR) systems. Telugu characters can be composed of many symbols joined together. OCR is the process of turning a document image into a text-editable one that may be used in other applications. It saves a great deal of time and effort by not having to start from scratch each time. There are hundreds of thousands of different combinations of modifiers and consonants when writing compound letters. Symbols joined to one another form a compound character. Since there are so many output classes in Telugu, there’s a lot of interclass variation. Additionally, there are not any Telugu OCR systems that take use of recent breakthroughs in deep learning, which prompted us to create our own. When used in conjunction with a word processor, an OCR system has a significant impact on real-world applications. In a Telugu OCR system, we offer two ways to improve symbol or glyph segmentation. When it comes to Telugu OCR, the ability to recognise that Telugu text is crucial. In a picture, connected components are collections of identical pixels that are connected to one another by either 4- or 8-pixel connectivity. These connected components are known as glyphs in Telugu. In the proposed research, an efficient deep learning model with Interrelated Tagging Prototype with Segmentation for Telugu Text Recognition (ITP-STTR) is introduced. The proposed model is compared with the existing model and the results exhibit that the proposed model’s performance in text recognition is high.
Field Experimental Study on Mechanical Properties of Frame Support Structure Composed of Subway Foundation Pit Retaining Pile and Steel Strut Rigid Joint
Authors: Huang Mingli , Zhien Zhang , Chen Bingyi , Wang Hongkun
Published: August 2022

In order to study the advantages of frame support structure composed of rigid joint between steel strut and retaining pile in restraining the lateral displacement of retaining structure and maintaining the stability of foundation pit, foundation pit failure test was carried out. Compared with the traditional support structure, which can only bear pressure composed of steel strut and retaining pile lap joint, the variation characteristics of pile lateral displacement and support axial force of frame support structure under the influencing factors, such as weak stratum, pit side loading, groundwater level rise, and support drop, are studied. The test results show that, compared with the traditional steel strut, the pile‐strut frame support structure can not only bear the compressive stress, but also the tensile stress caused by the lateral displacement of the top of the retaining pile outside the foundation pit. The overall stability is better, and the axial force distribution of each layer of support is more uniform so as to reduce the overall lateral displacement of the retaining pile. In the process of foundation pit collapse, the frame support structure will not have the problem of strut falling, which can maintain part of the support capacity, prolong the collapse time of retaining piles, strive for more escape time for front‐line construction workers, and reduce the number of casualties.
Research on the Optimization Technology of Mechanical Product Design Plan Based on Fuzzy Comprehensive Evaluation Analysis Method
Authors: Wang Zhijie , Cao Yan , Qiao Hu , Wu Yujia , Liu Miao
Published: August 2022

In the scheme design stage of mechanical products, several design solutions need to be evaluated so that the best design solution can be selected from them. Because the evaluation of mechanical product scheme design is a multilevel, multiattribute and contains many fuzzy models, fuzzy comprehensive evaluation becomes an advantageous model for the evaluation of mechanical product scheme design. In this article, a fuzzy comprehensive evaluation method is constructed, and a combination of the subjectivity of determining weights by hierarchical analysis method and the objectivity of determining weights by entropy value method is used to calculate the weights of evaluation indexes, and a combined assignment method is established to improve the reliability of the evaluation method. Then, the best solution is selected by calculating the comprehensive evaluation value of each product design solution. Finally, the validity, reasonableness, and feasibility of the evaluation model are verified through the evaluation and selection of three design solutions for a gearbox reducer, which also provides a new method for the evaluation and selection of other product design solutions.
[Retracted] Analysis of Legal Issues of Personal Information Protection in the Field of Big Data
Authors: Wang Chuyun , Guo Feifei , Ji Mengxuan
Published: August 2022

In the era of big data, while every citizen enjoys the convenience of the Internet, all kinds of information closely related to their personal and property are in a state of “streaking” for a long time. Personal information is frequently leaked, illegally misappropriated, and used. There are necessary requirements of network security. The risks and challenges faced by personal information in the context of big data increase. In the context of the rapid development of big data, the information is circulated in virtual cyberspace in the form of electronic data, and data sharing has become an important flow form of information circulation. It is an important link to realize the optimal allocation of network resources and realize the value of data. The great progress of the digital economy and artificial intelligence technology has greatly increased the demand for data, the speed of circulation has been further accelerated, and the potential value of data has been fully reflected. At present, the scope of personal information protected by Chinese laws is relatively narrow and is basically limited to the scope of privacy rights, which makes a large amount of information owned by individuals that do not belong to the category of personal privacy rights lack legal protection. Personal information is different from the characteristics of privacy rights. It is decided that the protection of personal information should be different from the protection of traditional personal privacy. To sum up, in view of this, this article attempts to analyze the new challenges faced by personal information protection in the era of big data from the perspective of law, combined with the background of the era of big data, from the legislative model, system design, supervision mechanism, industry self‐discipline, and other aspects. Exploration of the legislative framework for the protection of personal information in the era of big data in our country is done in order to find a realistic path that balances the development of big data technology and the protection of personal information.
Non‐Diskcyclicity of Bounded Composition Operators on the Little Bloch Space and the Besov Space
Authors: Zhou Hang , Liang Yuxia
Published: August 2022

In this paper, we show that there are no diskcyclic composition operators on the little Bloch space ℬ0 and the Besov spaces Bp.
Optimization of Intelligent Display Mode of Museum Cultural Relics Based on Intelligent Wireless Sensor Network
Authors: Shen Luolan
Published: August 2022

The traditional way of museum exhibition is physical exhibition, which is essentially restricted by the venue, time, space, and display conditions and is no longer applicable to the display form of modern museum exhibits. Therefore, with the development of a large number of modern technologies such as information technology, wireless sensor technology and image processing technology, the way of museum cultural relics display also tends to be more intelligent and intelligent. Based on this, this paper will set up corresponding gateway nodes, routing nodes, and corresponding terminal nodes for each node of the corresponding museum based on the intelligent wireless sensor network technology; transmit the audio impact information of the corresponding museum exhibits through the terminal nodes; and automatically send the node short address information of the corresponding information to the corresponding analysis end in real time for analysis and processing, and then based on the information characteristics of the corresponding exhibits, at the same time, combined with virtual fusion and human-computer interaction technology, a set of augmented reality application system for tourist mobile terminal is developed. Abandoning the disadvantages of traditional museum display methods, this paper creatively designs the corresponding museum heritage intelligent display workflow based on intelligent wireless sensor network through C/S architecture and finally realizes the enhancement effect of virtual reality on tourism terminals. In order to verify the superiority of the intelligent display mode of museum cultural relics based on intelligent wireless sensor network proposed in this paper, this paper compares it with the traditional display mode. The experimental results show that this paper has obvious advantages in the display comprehensiveness, visitor satisfaction, and display effectiveness, which further improves the effect of museum cultural relics display.
Data File Security Strategy and Implementation Based on Fuzzy Control Algorithm
Authors: Ren Jin
Published: August 2022

Today there are few studies on data file security strategies, but with the increase in information technology, the more the security of data files cannot be ignored. In this paper, based on the research of data file security policy, a model of data file security interaction based on a fuzzy control algorithm is proposed, and the correct rate of the model proposed in this paper is improved by about 1.5% under the traditional FTP server-based model.
Experimental Study and Numerical Analysis of Structural Performance of CRTS II Slab Track under Extreme High Temperature
Authors: Song Anxiang , Yao Guowen , Yu Xuanrui , Wang Yuerui , Wu Yifei
Published: August 2022

A ballastless track is susceptible to damage and even failure of structural components under the long-term effects of extremely high temperatures. In this paper, considering the influence of different constraint boundaries, a 1 : 4 scaled model of a ballastless track-bridge structural system was produced and placed in a large-sized environmental chamber. The thermal performance of the track structure was studied by carrying out temperature loading tests at extreme temperatures. In combination with the scaled-down model test data, a 3D nonlinear finite element model was established to investigate the damage evolution of broad-narrow joints under temperature gradient loading. The results are shown as follows: (1) the cement asphalt (CA) mortar layer has a hysteretic effect on the vertical temperature transfer. The most unfavorable structural part is between the track slab and the CA mortar layer of the track structure. (2) The constraint conditions accelerate the rate of temperature transfer, creating disturbances to the internal stresses of the track structure and amplifying the internal stresses induced by the environmental temperature increase. (3) Temperature and longitudinal stresses in the track’s structural layers are highly correlated. There is a significant quadratic regression between internal temperature and structural stresses in different extreme high-temperature environments. (4) As the temperature gradient load increases, the damage occurs at the junction of the broad-narrow joint and tends to expand towards the ends, which has little effect on the compression damage of the broad-narrow joint but significantly increases the tension damage. The research could provide useful guidance for the scientific operation and maintenance of the ballastless track in extreme high-temperature environments.
A Novel Metabolism-Related Gene Signature for Predicting the Prognosis of HBV-Infected Hepatocellular Carcinoma
Authors: Gao Zhenfu , Chen Jingyun , Zhou Yebin , Deng Pan , Sun Lu , Qi Jun , Zhang Ping
Published: August 2022

Metabolic reprogramming is one of the crucial hallmarks of cancer. Hepatocellular carcinoma (HCC) resulting from hepatitis B has various altered metabolic features. However, the impact of such alterations on the tumor microenvironment (TME) and immunotherapy efficacy is still unclear. Here, a prognostic signature of metabolism-related gene (MRG) composition was constructed, and the immune profile of different subgroups and potential response to immunotherapy were described. Based on the HCC gene dataset, we used weighted gene coexpression network analysis for identifying MRGs linked to hepatitis B. An MRG prognostic index (MRGPI) with two genes, ATIC and KIF2C, was constructed using Cox regression analysis, an independent prognostic factor. In addition, the model was validated using the GEO dataset. The immune profile and prediction of HCC response to immunotherapy in different subgroups were analyzed using CIBERSORT and TIDE. Based on the outcomes, the distributions of memory B cells, monocytes, resting mast cells, and M0 macrophages in TME were different with a greater benefit of immunotherapy in the low MRGPI risk group. In addition, the MRGPI risk groups showed substantial differences in sensitivity to conventional drug therapy. This study concludes that MRGPI is an effective biomarker for predicting the prognoses of patients with HCC resulting from hepatitis B virus infections and determining the efficacy of immunotherapy and conventional medical therapy.
Power Quality Improvement for Vehicle-to-Grid and Grid-to-Vehicle Technology in a Microgrid
Authors: Justin Fitrahsya , Peter Geno , Stonier Albert Alexander , Ganji Vivekananda
Published: August 2022

The demand for electric vehicles continues to grow, as evidenced by global sales of electric vehicles reaching 2.2 million in 2019 and more than doubling to 6.6 million in 2021. The rapid growth of renewable energies and electric vehicles (EVs) necessitates the use of microgrids, which are a promising solution to the problem of integrating large-scale renewables and EVs into the electric power system. Besides, the essential policy support provided by the government is an increase in the availability of public charging infrastructure for EVs. This research employs a fast-charging configuration of an off-board charger with DC energy transfer. Implementation of DC energy transfer for vehicle-to-grid and grid-to-vehicle technology in a microgrid due to DC charging’s unrestricted charger-rated power and rapid power transfer. However, the integration of EVs in the Microgrid system creates some operational challenges, which in this research are power quality issues such as harmonics in power systems that affect both utilities and consumers. The design models using the PI controller and the fuzzy controller based on MATLAB software are simulated to determine the control system’s effectiveness. These simulations assess the control system’s performance, and both approaches help improve the system’s performance power quality by minimizing the system’s total harmonic distortion (THD). According to the results, the fuzzy logic controller exceeded the traditional PI controller as demonstrated by minimizing the THD and also in terms of improving the waveform quality which achieved high accuracy with good performance. This research also utilized the fuzzy logic controller to control the power transfer between EVs and the microgrid, which differs from other research work, to achieve high system efficiency for the benefit of consumers.
Human-Terrestrial Wildlife Conflict in Ethiopia: A Systematic Review
Authors: Shanko Getahun , Tona Bekele
Published: August 2022

We conducted a review of 26 articles published between 2009 and 2021 to determine human-wildlife conflict based on spatial and temporal patterns, biological components, drivers of conflict, and mitigation methods used. We employed search, synthesis, appraisal, and analysis framework for review and VOSviewer software for network analysis. We included articles that only focused on relations between terrestrial wildlife and humans, while others deal with ecology, distribution, and biology of wildlife because it does not go with HWC. Forty-seven species of terrestrial vertebrates were reported in conflict-related studies, being Bovidae and Cercopithecidae the most frequently studied groups, of which eleven are found in threatened list species. The main drivers reported were land use change, proximity to protected areas, and illegal resource exploitation. In the management case, the use of traditional protection techniques such as fencing, guarding, and physical barriers was reported. About 178 keywords’ analysis revealed a focus on “coexistence,” “mitigation,” and “food security.” The literature focused mainly on larger mammals, led by Ethiopian authors, and excluded the social dimensions of HWC. Therefore, identifying conflict-prone species focuses on the social dimensions of coexistence, such as human attitudes towards terrestrial wildlife, and broadening the taxonomic and cultural breadth of HWC is required.
Logistics Information Traceability Mechanism of Fresh E-Commerce Based on Image Recognition Technology
Authors: Zhang Xin , Shao Pengfei
Published: August 2022

Logistics migration and movement require precise information updates for traceability and visibility of goods through E-commerce platforms. Computer vision and digital image processing techniques are used for visual identification and tracking through different warehouses and delivery points. In this article, an incessant visualized tracking scheme (IVTS) is designed for identifying and tracking E-commerce logistics throughout the migration points. This scheme endorsed computer vision technology for logistics recognition and labelled data detection. In this scheme, the labelled logistics data is verified for its similarity in different migrating locations and to the endpoint. Based on the dimensional features and regional-pixel similarity factor, it is verified using the deep neural network. This learning process identifies dimensional variations due to logistics displacement and position suppressing the similarity variations. It is performed based on the migration and information available to prevent tracking errors. For the varying locations and logistics displacement, the error pixel regions are identified and trained for possible similarity detection. The proposed scheme effectively improves visual accuracy, tracking maximization, and logistics detection by reducing dimensional errors.
Basketball Object Extraction Method Based on Image Segmentation Algorithm
Authors: Zhu Huachen , Liu Long
Published: August 2022

Finding your favorite videos from massive sports video data has become a big demand for users, accurate sports videos can better help people learn sports content, and the traditional data management and retrieval methods using text identifiers are difficult to meet the needs of users, so the research on the extraction of sports objects in sports videos is of great significance. This paper mainly studies and proposes the basketball object extraction method based on image segmentation algorithm and can accurately analyze the trajectory of the basketball target. By modeling the video frame of basketball game, the basketball object is selected for segmentation and extraction. The extracted basketball object can be used for tracking the target in the basketball video clip retrieval system. At the same time, the segmentation and extraction of the basketball object are also the core part in the basketball video clip retrieval framework. Combined with the characteristics of basketball video images in the database, the algorithm extracts the image block variance and contrast to form the training feature vector, and the correct segmentation rate on the database is higher than 95.2%. The results show that this method has a good effect on the segmentation and extraction of basketball objects in basketball videos.
The Impact of the Development of Modern Biotechnology and Nanotechnology on the Swimming Sports Industry
Authors: Liu Shuai , Guo Bailing
Published: August 2022

In today’s world, science and technology are developing rapidly, which has had a broad and profound impact on human society. After entering the twenty-first century, every ordinary person can feel the profound changes brought by modern science and technology to people’s daily life. In today’s society, the global economy is developing faster and faster, and the demand for sports is also increasing, bringing more and more consumers, which makes the sports industry an emerging industry with unlimited potential and expanding scale in the industrial economy. As one of the important events of modern competitive sports, swimming provides many opportunities and platforms for the development of Chinese competitive sports. Today, swimming is not only an Olympic sport but also a popular sport. Modern biotechnology and nanotechnology have an impact on all of our lives, but like other advanced technologies, their development inevitably involves uncertainty. This article focuses on the integration of nanotechnology and biotechnology to produce nanobiotechnology, the use of nanotechnology to address swimmers’ bodily functions, and the impact of its development on the field of swimming. The results found that compared with the normal group, the experimental group had an increase in the indexes of rest-fatigue-recovery stages, and the MPF value at rest increased significantly, from 90.1 to 111.3. As a popular sport among the people, swimming has also shown significant growth in the development of its social organization.
Magnetic Resonance Image Compilation Was Used in Conjunction with Prostate PI-RADS v2.1 Score Has Diagnostic Relevance for Benign and Malignant Prostate Lesions
Authors: Xu Wenjuan , Cao HaiYan , Du Fang , He Ling , Jiang FangLian , Hu ChunHong
Published: August 2022

Objective. To assess the diagnostic usefulness of magic in conjunction with PI-RADS v2.1 for prostate cancer malignant foci. Methods. A total of 202 lesions (97 transitional zone lesions and 105 peripheral zone lesions) from 198 people were investigated retrospectively using traditional MRI and magic images. Each lesion has a unique pathological consequence. Lesions T1, T2, and PD values were employed as magic observation markers. The locations of the lesions were aggregated, and the paired

t

-test and receiver operating characteristic curve (ROC) were employed to find the indices with statistical significance in separating benign from malignant prostatic nodules (+1 point) and (−1 point) respectively. Draw a ROC curve and compare it to the PI-RADS v2.1 score using the magic positive and negative indices as well as the PI-RADS v2.1 score. By comparing the ROC curves scored separately, the diagnostic efficiency of the two scoring approaches for benign and malignant prostate lesions was investigated. Results. T2 value has the highest diagnostic efficiency among the magic observation indices. T2 value of 77 ms for transitional zone lesions and T2 value of 89 ms for peripheral zone lesions are positive indices, whereas T2 value >77 ms and T2 value >89 ms are negative indexes. PI-RADS v2.1 combines one score and magic. In the transitional zone, the sensitivity, specificity, positive predictive value, and negative predictive value of the two scoring methods were 57.52, 87.70, 76.70, and 74.6 percent and 82.50, 73.68, 95.5, and 74.7 percent, respectively, and the AUC values were 0.735 and 0.846, respectively (

P
=
0.004

); in the peripheral zone, the AUC values were 86.15 percent, 68.42 percent, 82.4. Conclusions. Magic T2 value is a favorable sign for diagnosing benign and malignant prostate cancers when used in conjunction with PI-RADS v2.1. The end product exceeds PI-RADS v2.1 on its own, which is more useful in identifying benign and malignant prostate lesions, decreasing unnecessary puncture and alleviating patient pain.
The Application of Data Encryption Technology in Computer Network Communication Security
Authors: Liu Guanxiu
Published: August 2022

With the development of computer network and the popularization of information system, the security of databases, as platforms for centralized storage and sharing of information system data, has increasingly become a serious problem in the field of information security, so data encryption technology has come into people’s sight. However, the current data encryption technology still has certain shortcomings, such as the inconsistency of the code text of the encryption and decryption technology, and the low efficiency of decoding and encryption. The purpose of this paper is to study the application of data encryption technology in computer network communication to provide better suggestions and explore better methods for improving network communication security system. This article, through the analysis of the database threat model and database application system structure, puts forward a design scheme of database encryption system model. A complete database encryption system can be divided into five logic modules: a key storage module, key engine module, key information module, key management module, and data storage module, and provides an in-depth analysis of the various parts and implementation details related to these modules. Finally, the designed encryption system model is programmed to be implemented; with the help of online examination system, the function and performance of the encryption system were tested; and the transmission efficiency of data encryption is maintained at more than 95%, which proves the effectiveness of the system.
Environment-Friendly Behavior of New Agricultural Business Main Body Based on the Internet of Things
Authors: Li Xuelan , Jiang Jiyu
Published: August 2022

The Internet of Things economy is necessary for the reform of China’s economic industrial structure and international development, and it brings new opportunities and new challenges to the Chinese economy. The comprehensive informatization of the society is the prerequisite for the economic development of the Internet of Things. The Chinese government will adopt a strategy of simultaneous development to continue to accelerate the development of traditional agriculture while developing emerging strategic agriculture of the Internet of Things, accelerating the transformation of economic production methods. Family farming is a new type of agricultural business in the microeconomy. It is not only a producer and mobilizer of agricultural products but also an important carrier for implementing agricultural innovation technologies and promoting agricultural modernization. This article uses game theory, resource endowment theory, expectation theory, etc. to describe the impact mechanism of economies of scale, profit maximization, and environmental behavior on family farms from a game perspective and discusses the specific effects of resource endowments and psychological expectations. Through the research of the Internet of Things and the rural green energy cycle, this article applies it to the new agricultural business entities, thereby promoting the development of proenvironmental behavior analysis.
Environmental Sustainability Impact of Environmental Protection Regulations on the BRICS Countries
Authors: Liu Mingjun
Published: August 2022

The BRICS countries are also known as the BRICS, which are composed of five economies: China, Russia, India, Brazil, and South Africa. Of course, environmental issues are also included, because with the economic development of the five countries, the price paid is the environment. In response to this problem, in order to adapt the environmental problems arising in their own development to economic development, the BRICS countries have formulated corresponding laws and regulations to respond to existing or possible environmental problems. The most important purpose of this series of environmental protection laws is to achieve relatively stable and sustainable development in the five countries. This requires these environmental protection laws to have a sustainable impact on the environmental development of the BRICS countries. In order to conduct research on the impact of sustainable environmental laws that have been enacted, this article will use the analysis method of analyzing the relationship between the environmental protection regulations and economic development of the BRICS countries, as well as the relationship between the environmental protection laws and environmental sustainability development of the BRICS countries, and the impact of environmental sustainability based on empirical analysis. It assesses the impact on the sustainability of the environment of the BRICS countries under the auspices of environmental laws. Through the empirical analysis experiment of economic and environmental protection effects, the results obtained show that the comprehensive scores of environmental protection in the BRICS countries in 2018–2020 have been improved except Russia’s score. Among them, the improvement of China’s score is the most obvious, and the improvement of the ranking has reached 24. The results of this assessment show that, with the support of the corresponding environmental laws, sustainable impacts have been produced in the environment of the BRICS countries.
Image Classification Learning Method Incorporating Zero-Sample Learning and Small-Sample Learning
Authors: Sun Fanglei , Diao Zhifeng
Published: August 2022

At present, artificial intelligence algorithms based on deep learning have achieved good results in image classification, biometric recognition, medical diagnosis, and other fields. However, in practice, many times researchers are unable to obtain a large number of samples due to many limitations or high sampling costs. Therefore, image sorting zero-sampling order research algorithms have become the central engine of intelligent processing and a hot spot for current research. Because of the need for the development of deep learning prediction capability, coupled with the emergence of time and technical-level drawbacks, the advantages of zero-sample and small-sample are gradually emerging, so this paper chooses to fuse the learning methods of both for image recognition research. This paper mainly introduces the current situation of zero-sample and small-sample learning and summarizes the learning of zero-sample and small-sample. And the meaning of zero-sample learning and small-sample learning and the classification of the main learning methods are introduced and compared and outlined, respectively. Finally, the methods of zero-sample and small-sample learning are fused, the design is introduced and analyzed, and the future research directions are prospected according to the current research problems.