bluuebunny/crossref_metadata_2025 huggingface dataset:
Minimization of Nonproductive Time in Drilling: A New Tool Path Generation Algorithm for Complex Parts
Authors: Khodabakhshi Z. , Hosseini A. , Ghandehariun A.
Published: June 2022

In computerized tool path programming, the operator/user can generate the tool path based on the shape and geometry of the part to be produced by choosing from a set of predefined strategies available in the library of Computer Aided Manufacturing (CAM) software. These tool paths are typically not optimum, specifically for complex geometries. This paper employed Travelling Salesman Problem (TSP) as a foundation to propose a new tool path optimization algorithm for drilling to minimize the tool path length and subsequently reduce the time spent on nonproductive movements. The proposed algorithm was solved using local search approach in the presence of multiple constraints including geometric obstacles and initial location of tool origin. The outcome was a near-optimum tool path for drilling operations with no collision with workpiece features. The computational efficiency of the proposed algorithm was also compared with other methods in available literature using a standard workpiece as a benchmark. The results confirmed that for given examples, the near-optimum collision-free tool paths using the developed model in this paper were almost 50% shorter than the tool path generated by a commercial CAM software.
Do CIOs Matter in the Face of Exogenous Shocks? An Examination Through Upper Echelon Theory
Authors: Taylor Joseph , Sahaym Arvin , Vithayathil Joseph
Published: June 2022

Information Technology has taken a prominent role in firm investments, yet there is considerable variation in returns in technology-based expenditures. We posit that the technology leader such as the CIO or CTO is a valuable resource and plays a critical role when the position is endowed with power. Our analysis shows how a technology leader’s influential presence affects firm performance, particularly in the presence of an IT-related exogenous shock. Using cross-industry data, we find that firms with powerful technology leaders generate higher sales growth, and furthermore, in the presence of exogenous shocks, markets reward firms having powerful technology leaders.
Constant Gaussian curvature, FLRW conditions and a universe without matter
Authors: Boskoff Wladimir-Georges
Published: June 2022

The problem of FLRW universes can be seen in the excellent works of A. Friedmann, G. Lemaître, H. P. Robertson, A. G. Walker. The key of obtaining FLRW universes with or without cosmological constant is related to the special form of the contravariant energy–momentum tensor which describes a perfect fluid with components [Formula: see text] because such a “matter” leads to FLRW conditions [Formula: see text] which allow to obtain a texture compatible with Hubble law. The results obtained in the works presented as references show very complete analysis about how the constant curvature 2D metric [Formula: see text] can create possible universes and their evolution. Can we expect to have some other FLRW universes if we use a 2D spatial part as [Formula: see text]?

The answer is yes and we prove the special role of the constant ratio [Formula: see text] in the creation of FLRW universes. The solutions obtained lead to FLRW universes which come from surfaces having constant Gaussian curvature related by the previous [Formula: see text] from the rule [Formula: see text]. Therefore, in the case of the 2D metrics [Formula: see text], only the ones having constant Gaussian curvature create FLRW universes. In fact, we find all possible FLWR-type solutions of Einstein field equations coming from constant Gaussian curvature geometries. We complete our study about possible FLRW universes with an example of a spacetime that cannot be “filled” with matter using the above FLRW conditions. This becomes a new example of universe without matter satisfying the Einstein’s field equation with cosmological constant.
Novel results on attractivity of a neoclassical growth system incorporating multiple pairs of time-varying delays
Authors: Fan Weiping , Cao Qian
Published: June 2022

In this paper, we analyze the global dynamics of a neoclassical growth system incorporating patch structure and multiple pairs of time-varying delays. First, we derive the global existence, positiveness and boundedness of solutions for the addressed system. Then, by employing some novel differential inequality analyses and the fluctuation lemma, both delay-independent and delay-dependent criteria are established to ensure that all solutions are convergent to a unique positive equilibrium point vector, which does not possess the same components. Our results supplement and improve some existing results. Ultimately, some numerical examples are afforded to prove the effectiveness and feasibility of the theoretical findings.
A graph associated with modules over commutative rings
Authors: Mahdavi Lotf Ali , Rad Parastoo Malakooti
Published: June 2022

Let [Formula: see text] be a commutative ring with identity and [Formula: see text] be a unitary [Formula: see text]-module. We associate an undirected simple graph to an [Formula: see text]-module [Formula: see text] denoted by [Formula: see text] with the vertex set [Formula: see text] and two distinct vertices [Formula: see text] and [Formula: see text] are adjacent if and only if there exists the nonzero element [Formula: see text] in [Formula: see text] such that [Formula: see text] or [Formula: see text]. In this paper, we investigate the interplay between the graph-theoretic properties of [Formula: see text] and algebraic properties of the module [Formula: see text]. We study the connectivity and completeness of [Formula: see text]. Also, the diameter and the girth of this graph are determined. We prove that if [Formula: see text] is an [Formula: see text]-module with [Formula: see text], then [Formula: see text] has a cycle or [Formula: see text], for some [Formula: see text]. Also, we show that if [Formula: see text] is a multiplication [Formula: see text]-module and [Formula: see text] is a planar graph, then every prime submodule of [Formula: see text] is non-faithful.
Detour global domination for splitting graph
Authors: Jayasekaran C. , Ashwin Prakash S. V.
Published: June 2022

In this paper, we introduced the new concept detour global domination number for splitting graph of standard graph. The detour global dominating sets in some standard and special graphs are determined. First we recollect the concept of splitting graph of a graph and we produce some results based on the detour global domination number of splitting graph of star graph, bistar graph and complete bipartite graph. A set [Formula: see text] is called a detour global dominating set of [Formula: see text] if [Formula: see text] is both detour and global dominating set of [Formula: see text]. The detour global domination number is the minimum cardinality of a detour global dominating set in [Formula: see text].
Magnetic Field and Radial Force Analysis of Six-Phase Rotary Machine
Authors: Dong Ziwei , Yan Liang , Gerada Chris
Published: June 2022

Six-phase permanent magnet synchronous machine and the control system are also widely used in industry, precision instruments and aerospace. However, most PMSMs employ magnet patterns either in alternatively radial magnetization or Halbach array, which may constrain the performance improvement in a certain degree. Therefore, a novel six-phase trapezoidal Halbach magnet array (THMA) is proposed in this paper. Six-phase permanent magnet synchronous machines (PMSMs) can reduce the harmonic components of magnetic flux in air gap, and decrease the iron loss and electromagnetic vibration caused by harmonic torque. Thus, it helps to improve the working efficiency and depress the torque ripple of the electrical machine. Dual three-phase windings are employed for the stator design to further improve the power density and reliability of the machine. Six-phase vector model of the machine is built based on dual dq control. It can minimize the electric coupling, magnetic coupling and thermal coupling. The radial electromagnetic force of the machine under load or no load is extracted, then the harmonic decomposition of the radial electromagnetic force for the spatial with time Fourier decomposition is carried out to obtain the force amplitude of different orders which is conducive to analyze the vibration characteristics of the machine.
Energy-Efficient Database Systems: A Systematic Survey
Authors: Guo Binglei , Yu Jiong , Yang Dexian , Leng Hongyong , Liao Bin
Published: June 2022

Constructing energy-efficient database systems to reduce economic costs and environmental impact has been studied for 10 years. With the emergence of the big data age, along with the data-centric and data-intensive computing trend, the great amount of energy consumed by database systems has become a major concern in a society that pursues Green IT. However, to the best of our knowledge, despite the importance of this matter in Green IT, there have been few comprehensive or systematic studies conducted in this field. Therefore, the objective of this article is to present a literature survey with breadth and depth on existing energy management techniques for database systems. The existing literature is organized hierarchically with two major branches focusing separately on energy consumption models and energy-saving techniques. Under each branch, we first introduce some basic knowledge, then we classify, discuss, and compare existing research according to their core ideas, basic approaches, and main characteristics. Finally, based on these observations through our study, we identify multiple open issues and challenges, and provide insights for future research. It is our hope that our outcome of this work will help researchers develop more energy-efficient database systems.
On Dynamically Pricing Crowdsourcing Tasks
Authors: Miao Xiaoye , Peng Huanhuan , Gao Yunjun , Zhang Zongfu , Yin Jianwei
Published: June 2022

Crowdsourcing techniques have been extensively explored in the past decade, including task allocation, quality assessment, and so on. Most of professional crowdsourcing platforms adopt the
fixed pricing scheme
to offer a fixed price for crowd tasks. It is
neither
incentive for crowd workers to produce good performance,
nor
profitable for the requester to gain high utility with low budget. In this article, we study the problem of pricing crowdsourcing tasks with optional bonuses. We propose a dynamic pricing mechanism, named
CrowdPricer
for incentively delivering bonuses to the crowd workers of completing tasks, in addition to offering a base payment for completing a task. We leverage a deep time sequence model to learn the effect of bonuses on workers’ quality for crowd tasks.
CrowdPricer
makes decisions on whether to provide bonuses on workers, so as to maximize the requester’s utility in expectation. We present an efficient
bonus delivery
algorithm under the help of beam search technique, in order to efficiently solve the decision making problem. Extensive experiments using both a real crowdsourcing platform and simulations demonstrate that
CrowdPricer
yields the higher utility for the requester. It also obtains more correct crowd answers than the state-of-the-art pricing methods.
Fault Diagnosis Using Data Fusion with Ensemble Deep Learning Technique in IIoT
Authors: Venkatasubramanian S , Raja S , Sumanth V , Dwivedi Jaiprakash Narain , Sathiaparkavi J , Modak Santanu , Kejela Mandefro Legesse
Published: June 2022

Detecting the breakdown of industrial IoT devices is a major challenge. Despite these challenges, real-time sensor data from the industrial internet of things (IIoT) present several advantages, such as the ability to monitor and respond to events in real time. Sensor statistics from the IIoT can be processed, fused with other data sources, and used for rapid decision-making. The study also discusses how to manage denoising, missing data imputation, and outlier discovery using preprocessing. After that, data fusion techniques like the direct fusion technique are used to combine the cleaned sensor data. Fault detection in the IIoT can be accomplished by using a variety of deep learning models such as PropensityNet, deep neural network (DNN), and convolution neural networks-long short term memory network (CNS-LSTM). According to various outcomes, the suggested model is tested with Case Western Reserve University (CWRU) data. The results suggest that the method is viable and has a good level of accuracy and efficiency.
Real-Time Monitoring of College Sports Dance Competition Scenes Using Deep Learning Algorithms
Authors: Yang Fei , Wu GeMuZi , Shan HongGang
Published: June 2022

In order to improve the real-time detection effect, therefore, a research on real-time scene detection of sports dance competition based on deep learning is proposed. The collected scene image is grayed by using the weighted average method, and the best image interpolation is calculated by using the deep learning method, so as to realize the smooth processing of sawtooth and mosaic information generated by panoramic mapping. After selecting the cube model, the processed scene information is projected to the visual plane to construct the panorama of the competition scene. Finally, combined with the three-frame difference, the changes between adjacent image frames are calculated to obtain the moving target. The test results show that the motion detection accuracy of professional dancers can reach more than 75.0% and that of amateur dancer can reach more than 64.2%.
Bi-Finite Difference Method to Solve Second-Order Nonlinear Hyperbolic Telegraph Equation in Two Dimensions
Authors: Raslan K.R. , K Ali Khalid. , Al-Jeaid Hind K , Shaalan M.A.
Published: June 2022

This study introduces a computational scheme by the bi-finite difference method (Bi-FDM) to solve the hyperbolic telegraph equation in two dimensions. The proposed numerical method converts nonlinear two-dimensional hyperbolic telegraph equation of second order to difference equations that can be solved by the Mathematica program. Consistency and stability of the proposed scheme are discussed and found to be accurate of

O

h

x

2

+

h

y

2

+

Δ
τ

2

and conditionally stable, respectively. The efficiency and accuracy of Bi-FDM have been shown by comparing the numerical results of the presented problems with the exact solutions and other numerical techniques.
Ecological Village Planning and Green Building Design from the Perspective of Rural Environmental Aesthetics
Authors: Wang Hua
Published: June 2022

The society is making continuous progress, and the results of urban planning and construction are obvious to all. However, there are still many problems in the planning and construction of villages and towns, resulting in relatively backward development. The purpose of this article is to study the planning of ecological villages and towns and the design of green buildings from the perspective of rural environmental aesthetics. This article briefly introduces the principles and problems of ecological village planning through literature research and investigation and puts forward some suggestions on ecological village planning. Through investigation and experiment, the energy problem, structural material problem, and planning problem in green building design are analyzed. The results show that due to various limitations, the use and promotion of solar energy are blocked. Only by helping farmers solve their difficulties can clean energy be used in green buildings and the burning of straw be reduced. Nationwide, the proportion of brick-concrete structures, brick-wood structures, and reinforced concrete structures in rural housing reached 57.2%, 26%, and 12.5%, respectively. Many rural buildings pursue reinforced concrete structures, but brick and wood structures may be more suitable for most rural areas.
Relationship between Financial Asset Allocation, Leverage Ratio, and Risk‐Taking of Small‐ and Medium‐Sized Enterprises in China: Taking Environment‐Related Industries as an Example
Authors: Chen Qing
Published: June 2022

With the improvement of environmental policies and industry requirements for enterprise production and management, small‐ and medium‐sized enterprises in environment‐related industries were also changing. It was known from the existing research that the investment allocation of assets of small‐ and medium‐sized enterprises was closely related to risk and return, and the leverage ratio of enterprises affected the risk‐taking level of enterprises. In the process of sustainable development, enterprises will inevitably bear certain risks, but excessive risk‐taking will bring all kinds of uncertainty and bankruptcy risk to the expected income and future cash flow of enterprises. Therefore, taking small‐ and medium‐sized enterprises in environment‐related industries as an example, this paper put forward relevant assumptions by analyzing the interaction between the existing enterprise financial asset allocation, risk‐taking level and leverage ratio. In order to facilitate empirical analysis, A‐share listed companies in environment‐related industries in Shanghai and Shenzhen stock exchanges, small‐ and medium‐sized board and GEM listed companies in Shenzhen stock exchange from 2007 to 2019 were selected as research samples. These data came from the information open platform for small‐ and medium‐sized enterprises in environment‐related industries, the research reports of third‐party consulting companies and CSMAR and Wind databases. The empirical results showed that the allocation of financial assets had a significant impact on the level of risk‐taking, and there was a U‐shaped relationship between them when other conditions remained unchanged. At the same time, the financial asset allocation of small‐ and medium‐sized enterprises in Chinese environment‐related industries had a significant impact on the enterprise leverage ratio. Under other conditions unchanged, there was a U‐shaped relationship between the two. In addition, leverage played an intermediary role in the relationship between financial asset allocation and risk‐taking level. In addition to directly affecting the allocation of financial assets, it can also indirectly affect the risk‐taking level of enterprises through leverage ratio.
Machine Learning of Dose-Volume Histogram Parameters Predicting Overall Survival in Patients with Cervical Cancer Treated with Definitive Radiotherapy
Authors: Xu Zhiyuan , Yang Li , Liu Qin , Yu Hao , Chen Longhua
Published: June 2022

Purpose. To analyze the effects of dosimetric parameters and clinical characteristics on overall survival (OS) by machine learning algorithms. Methods and Materials. 128 patients with cervical cancer were treated with definitive pelvic radiotherapy with or without chemotherapy followed by image-guided brachytherapy. The elastic-net models with integrating DVH parameters and baseline clinical factors, only DVH parameters and only baseline clinical factors were constructed in 5-folds cross-validations for 100 iteration bootstrapping, and then were compared using concordance index (C-index) criteria. Finally, the selected important factors were used to build multivariable Cox-pH models for OS and also shown in nomograms for clinical usage. Results. The median OS occurred was 25.78 months with 25 (19.53%) deaths. The elastic-net models integrating clinical and DVH factors had the best prediction performances (C-index 0.76 in the train set and C-index 0.74 in the test set). Three important factors were selected, including baseline hemoglobin level as the protective factor, primary tumor volume (GTV_P) volume, and body V5 as the risk factors. The final multivariable Cox-pH models were constructed using these important factors and had prediction performance (C-index: 0.78, 95%CI: 0.73–0.81). Conclusions. This is the first attempt to establish elastic-net models to study the contributions of DVH parameters for predicting OS in patients with cervical cancer. These results can facilitate individualized tailoring of radiation treatment in cervical cancer patients.
Renal Protective Effects of Melatonin in Animal Models of Diabetes Mellitus-Related Kidney Damage: A Systematic Review and Meta-Analysis
Authors: Luo Qian , Cai Yuzi , Zhao Qihan , Jiang Yuhua , Tian Lei , Liu Yuning , Liu Wei Jing
Published: June 2022

Diabetic nephropathy (DN)—chronic kidney damage caused by hyperglycemia—eventually develops into end-stage renal disease (ESRD). Melatonin is a powerful antioxidant that has a wide range of biological activities. Potentially helpful effects of melatonin on diabetic kidney disease have been found in several studies. However, its protective mechanisms are not clear and remain to be explored. In this review (CRD42021285429), we conducted a meta-analysis to estimate the effects and relevant mechanisms of melatonin for diminishing renal injuries in diabetes mellitus models. The Cochrane Library, PubMed, and EMBASE databases up to September 2021 were used. Random- or fixed-effects models were used for calculating the standardized mean difference (SMD) or 90% confidence interval (CI). The risk of bias was estimated using the SYRCLE’s RoB tool. Statistical analysis was conducted with RevMan. A total of 15 studies including 224 animals were included in the analysis. The experimental group showed a remarkable decrease in serum creatinine (

P
=
0.002

), blood urea nitrogen (

P
=
0.02

), and urinary albumin excretion rate (UAER) (

P
<
0.00001

) compared with the control group, while the oxidative stress index improved. The experimental group also showed a remarkable increase in superoxide dismutase (

P
=
0.21

), glutathione (

P
<
0.0001

), and catalase (

P
=
0.04

) and a remarkable decrease in MDA (

P
<
0.00001

) content compared with the control group. We concluded that melatonin plays a role in renal protection in diabetic animals by inhibiting oxidative stress. Moreover, it should be noted that fasting blood glucose was reduced in the experimental group compared with the control group. The kidney and body weights of the animals were not decreased in the diabetic animal model compared with the control group.
Information Security Countermeasures for Big Data Platforms Based on Cloud Computing
Authors: He Jing , Sun Yu
Published: June 2022

Nowadays, with advanced information technology, cloud computing, big data, and other technologies are widely used in various activities, and their value has been proven and attracted people’s attention. This article aims to study the challenges faced by the development of national information security in the context of big data in the new era. While the big data platform brings convenience to social life, it will also have a major impact on national information security. In order to protect information security, big data needs to be managed to improve the quality and efficiency of its use. As a result of empirical analysis, information security in this environment is a personal issue as well as an important social issue. The way to solve this problem naturally starts from increasing people’s awareness of preventing personal information and increasing the protection of commercial information, but it is necessary to improve relevant government laws and regulations, improve the government’s information supervision capabilities, and clean up and optimize for the government. The unique role of the information environment is more important and more fundamental. In 2018, a total of 3 billion pieces of data were leaked worldwide, an increase of 70% compared to 2017. Information leakage occurs almost all the time, so we should effectively prevent information from being stolen.
On Orthogonal Coupled Fixed Point Results with an Application
Authors: Mani Gunaseelan , Gnanaprakasam Arul Joseph , Javed Khalil , Kumar Santosh
Published: June 2022

In this manuscript, owing to the concept of orthogonal coupled contraction mappings type I and II, we prove coupled fixed point theorem in orthogonal metric spaces. In order to strengthen our main results, a suitable example is presented. Moreover, the results we obtained supplement and improve previous research findings. A fruitful application is also supplied to endorse our outcomes.
An Efficient Computing Offloading Scheme Based on Privacy-Preserving in Mobile Edge Computing Networks
Authors: Pang Shanchen , Sun Huanhuan , Wang Min , Wang Shuyu , Qiao Sibo , Xiong Neal N.
Published: June 2022

Computation offloading is an important technology to achieve lower delay communication and improve the experience of service (EoS) in mobile edge computing (MEC). Due to the openness of wireless links and the limitation of computing resources in mobile computing process, the privacy of users is easy to leak, and the completion time of tasks is difficult to guarantee. In this paper, we propose an efficient computing offloading algorithm based on privacy-preserving (ECOAP), which solves the privacy problem of offloading users through the encryption technology. To avoid the algorithm falling into local optimum and reduce the offloading user energy consumption and task completion delay in the case of encryption, we use the improved fast nondominated sorting genetic algorithm (INSGA-II) to obtain the optimal offloading strategy set. We obtain the optimal offloading strategy by using the methods of min-max normalization and simple additive weighting based on the optimal offloading strategy set. The ECOAP algorithm can preserve user privacy and reduce task completion time and user energy consumption effectively by comparing with other algorithms.
Influence of the Athlete’s Training Physical State Test Based on the Principle of Artificial Intelligence Sensor
Authors: Song Zhanbing , Tian Caixia
Published: June 2022

Artificial intelligence is the study of the laws of human intelligent activities, the construction of artificial systems with certain intelligence, and the study of how to make computers perform tasks that required human intelligence in the past. Basic Theories, Methods, and Techniques. With the maturity of the highly integrated hardware technology, the rapid development of sensor technology provides a material basis for the study of sports states based on smart terminals, and the mature model method theory provides a theoretical research basis for the research. The working principle of the sensor is to convert the specific measured signal into a certain “available signal” according to a certain rule through the sensitive element and the conversion element and output it to meet the requirements of information transmission, processing, recording, display, and control. In order to deeply study the application of artificial intelligence sensor theory in athlete training physical condition testing, this article uses theoretical analysis method, formula image combination method, and real person survey method, collects samples, analyzes artificial intelligence sensor, and streamlines the algorithm. In studying the accuracy of smart sensors on athlete training tests, a total of 9 athletes, 4 females, and 5 males are selected. Each experimenter performed three actions of running, jumping, and squatting 10 times, with an interval of more than 20 s. The results showed that the recognition accuracy of running in this paper was 98.51%, and the recognition accuracy of jumping and squatting was 92.59% and 93.33%; we have achieved more than 92% recognition rate for the three kinds of actions. On further study of the real-time performance of the sensor, the average response time of the algorithm is the average value obtained from 80 experimental records in this paper. The average response time of the algorithm proposed in this paper is within 1.5 s. Since the falling process occurs within 2.1 s, the recognition algorithm proposed in this paper has high real-time performance. It is basically realized that starting from the theory of artificial intelligence sensors, a high-precision sensor that can be applied to athlete training is designed.
Alternative Water Resources Selection to Supply Drinking Water in Flood Disasters by Multicriteria Decision‐Making Techniques (DANP and VIKOR)
Authors: Zamani Aman Allah , Abbasi Hamid Reza , Alipour Vali , Peyravi Mahmoudreza , Shojaei Payam , Goli Ali , Mohammadinia Leila
Published: June 2022

Background. Emergency is generally caused by natural disaster and infectious disease outbreaks, or it is man‐made. Floods are natural phenomena that generally appear in multiple parts of the world. Flooding is one of the most destructive naturally occurring environmental hazards and can cause public, infrastructural, and environmental damage. The purpose of this study is to select alternative water resources for supplying Bandar Abbas in flood disasters by multicriteria decision‐making techniques. Methods. Information required includes possible water resources alternative for flood, quantitative and qualitative characteristics of the water resources, climatic circumstances, and demographic information used in organizations data and previous studies. After selecting and proposing water resources alternative for Bandar Abbas in flood, the subcriteria were weighed applying DANP (DEMATEL‐ANP) techniques and water resources were prioritized with the VIKOR technique. According to the network structure and internal and external dependence of the criteria and subcriteria, the advantages of DANP in calculating weights have been used to adapt to more real‐world problems. The VIKOR technique was developed for multicriteria optimization of complex systems. Results. After reviewing and extracting the criteria from various studies, 9 main criteria and 44 subcriteria were defined to select water resources in disasters and emergencies. According to field studies and related organizations’ information, the proposed water resources for Bandar Abbas to use in flood disasters include humidity, sea (Persian Gulf), Sarkhoon plain, and wastewater treatment plant of Bandar Abbas. Conclusion. Results showed that the optimal water resources for Bandar Abbas in flood disasters are the sea and wastewater treatment plant effluent (after advanced treatment). The study proposed appropriate model to select optimal water resources for various natural disasters in different geographical areas. This model can help officials and decision‐makers to plan for drinking water supply from disaster‐prone areas before disasters occur.
Prevalence and Clindamycin Resistance Profile of Staphylococcus aureus and Associated Factors among Patients Attending the University of Gondar Comprehensive Specialized Hospital, Gondar, Northwest Ethiopia
Authors: Ambachew Aklilu , Gebrecherkos Teklay , Ayalew Getnet
Published: June 2022

Clindamycin can serve as an alternative treatment for staphylococcal infections. Routine susceptibility tests may fail to determine inducible type clindamycin resistance and can be a source of failure in clinical therapeutics. Therefore, this study aimed to determine Staphylococcus aureus (S. aureus) prevalence, inducible clindamycin resistance pattern, and associated factors among patients attending the University of Gondar Comprehensive Specialized Hospital, Gondar, northwest Ethiopia. Methods. A cross-sectional study was conducted from January to April 2018. Clinical samples were inoculated on appropriate culture media. Standard bacteriological tests, including Gram stain, catalase, and coagulase tests, identified the presence of S. aureus. The antimicrobial susceptibility tests and the D-test were performed by using the Kirby–Bauer disk diffusion technique on the Mueller–Hinton agar. The D-test was performed using clindamycin (CLI) 2 ug and erythromycin (ERY) 15 ug disks located approximately 15 mm apart, and the cefoxitin susceptibility test was used to characterize methicillin-resistant S. aureus (MRSA). The association between S. aureus infection and different variables was assessed using bivariate and multivariate analysis. A

P

value <0.05 was considered statistically significant. Result. Of 388 study participants, the overall prevalence of S. aureus was 17% (66/388). Of these, the inducible type of clindamycin resistance was 25.8% (17/66) and 21.2% (14/66) were MRSA. All isolates were susceptible to chloramphenicol and resistant to tetracycline. A family size of 4–6 (AOR = 2.627, 95% CI (1.030–6.702)) and >7 (AOR = 3.892, 95% CI (1.169–12.959)), inpatient study participants (AOR = 3.198, 95% CI (1.197–8.070)), illness in the previous 4 weeks (AOR = 2.116, 95% CI (1.080–4.145)), and a history of chronic disease (AOR = 0.265, 95% CI (0.094–0.750)) were likely to have S. aureus infection. Conclusion. This study shows a considerable high magnitude of MRSA and inducible clindamycin resistance S. aureus isolates. To rule out clindamycin susceptibility testing, the D-test should be routinely performed.
LNCRNA XIST Inhibits miR-377-3p to Hinder Th17 Cell Differentiation through Upregulating ETS1
Authors: Yao Chen , Li Chao , Liu Zhijia , Xiao Li , Bai Hongwei , Shi Bingyi
Published: June 2022

Background. Th17 cell differentiation is involved in the development and progression of many diseases, such as rheumatoid arthritis and systemic lupus erythematosus. Present study mainly focused on the role of LINC-XIST in Th17 cell differentiation. Methods. The naïve CD4+ T cells were isolated from human whole blood. Cells were cultured under Th17 cell-polarizing condition for 6 days. The expression of LINC-XIST and miR-153-3p was measured by qPCR. The relationship between LINC-XIST, miR-153-3p, and ETS1 was predicted by TargetScan website and authenticated by luciferase reporter assay. ELISA assays were conducted to evaluate the IL-17 concentration. Western blot was utilized to measure the protein expression of ETS1. Th17 cell frequency was examined by flow cytometry. Results. The expression of XIST markedly decreased and miR-153-3p expression markedly increased with Th17 cell differentiation. The mRNA expression of IL-17, IL-17 concentration, and Th17 cell frequency were observably decreased in overexpressed LINC-XIST group. Luciferase reporter assay authenticated that miR-153-5p was directly regulated by LINC-XIST. miR-153-3p inhibitor observably decreased IL-17 concentration, mRNA expression of IL-17, and Th17 cell frequency while si-XIST reversed this impact. ETS1 was confirmed to be regulated by miR-153-5p via luciferase reporter assay. In addition, ETS1 markedly decreased IL-17 mRNA expression, IL-17 concentration, and Th17 cell frequency while miR-153-5p mimic reversed this impact. Conclusion. LNCRNA XIST inhibited miR-377-3p to hinder Th17 cell differentiation through upregulating ETS1.
Image Geolocation Method Based on Attention Mechanism Front Loading and Feature Fusion
Authors: Lu Huayuan , Yang Chunfang , Qi Baojun , Zhu Ma , Xu Jingqian
Published: June 2022

Image geolocation is an important technique for robotics and autonomous systems. The existing methods mainly extract local features from images directly and use global descriptors, which are aggregated by these local features, to retrieve candidate references from all references. Thus, the training efficiency is affected by the image noises and the accuracy is so limited that the further verification is extremely time consuming. To address these issues, this work proposes an image geolocation framework, which adds the noise filtering layer before local feature extraction. Based on this framework, an image geolocation method based on attention mechanism front loading and feature fusion is designed. In the noise filtering layer, the proposed method uses triplet attention to denoise images thus leading to higher training efficiency. In the feature aggregation layer, an improved SPP (spatial pyramid pooling) is designed to extract the local factors reflected by the position relationships among local features. Then, the local factors are incorporated with the global factors extracted by NetVLAD. The fused descriptors contain not only the statistic of the geometric elements but also the position relationships among them. The experimental results show that the proposed method outperforms NetVLAD in terms of the training convergence round and Recall@

N

(

N
=
1
,
5
,
10
,
20

); especially, the convergence round of Recall@5 reduces from 25 to 10, the convergence round of Recall@10 reduces from 25 to 7, Recall@1 increases from 79.45% to 84.01%, and Recall@5 increases from 90.10% to 92.81%.
Structural Design and Electrical Characteristics Analysis of Mid-Load Whip Antenna
Authors: Xiu Menglei , Li Lihua , Feng Shimin
Published: June 2022

In order to facilitate the integration of the offshore surface antenna and reduce the manufacturing cost, the resonance shortening length and omnidirectional radiation performance of a centrally loaded whip antenna are analyzed. By calculating the impedance characteristics of each part of the midload whip antenna, the shortened length of the antenna in the resonance state is obtained; the superimposed field strength of the midload whip antenna to the far field is calculated and its radiation performance is analyzed; the simulation is carried out by using FEKO electromagnetic simulation software. Through the field test, the reflection coefficient and resonant frequency of the antenna before and after shortening are compared, and the directivity of the midload whip antenna and the traditional whip antenna is compared. The simulation and experimental results show that under the preset frequency of 75 MHz, the reflection coefficient of the shortened midload whip antenna decreases by 4.414 dB and 19.09 dB, respectively. The optimal operating frequency is about 68.6 MHz–79.4 MHz, and the bandwidth is 10.8 MHz. Compared with the traditional whip antenna, the midload whip antenna at the radiation null point receives a larger field strength.
Application of CAD/CAM Technology in Electrochemical Relief Design and Processing of Ceramic Art
Authors: Li Hongyan
Published: June 2022

Ceramic relief modeling design and CNC machining programming have a wide range of applications in industrial production and daily life. In view of the actual needs of enterprises, this research studies the CAD simulation technology of ceramic relief and achieves the modeling of other pieces of relief based on the geometric outline of the plane breakthrough. According to geometric relief modeling, bitmap relief modeling, tool path selection, and relief simulation processing, the establishment of a ceramic relief model is realized. Finally, the simulation processing is carried out on the ArtCAM software platform, and reasonable processing parameters are obtained to realize the CNC engraving processing of ceramic relief. The experimental results show that the machining efficiency of the ceramic relief model established in this study is improved by 11.3% and 42.8%, respectively, compared with the two traditional methods, which verifies the correctness and superiority of the designed model.
Tree Species Diversity in a Naturally Regenerated Secondary Forest in the Ruhande Arboretum, Rwanda
Authors: Mugunga Canisius Patrick , Mindje Mapendo , Cyuzuzo Henriette Abimana , Uwiringiyimana Jeannine , Mind’je Richard
Published: June 2022

This work studied the vegetation in a seven-hectare self-regenerated and protected forest about nine decades-old located in a previously cultivated site in the Ruhande Arboretum to identify woody species and their diversity. Ten parallel transects were established at 34 m intervals, leaving 25 m on either side to avoid an edge effect. Along transects, circular 16 m diameter plots spaced 20 m apart were established, making a total of 56 plots. In each plot, woody species were recorded and those with heights >2 m had their diameter at breast height measured. Phytosociological data including basal area, density, and frequency and their respective relative values were computed and used to determine species and family importance value indices within each plot. Across all plots, twenty-eight genera in 17 families were identified and 844 plants were recorded, including 755 trees and 89 shrubs, with most trees found in smaller diameter classes. Across all plots, only one Markhamia lutea tree was in the 50–60 cm diameter class and one Polyscias fulva was in the >90 cm diameter class. Of all woody species, Polyscias fulva was the most dominant since it had individuals with the biggest diameter. The number of individuals per family across all plots ranged from one for Cupressaceae, Dracaenaceae, Moraceae, and Solanaceae to 414 for Bignoniaceae. Across all plots, the diameter at breast height ranged from 1.8–97 cm. The species importance value index ranged from 0.3–41.8 for Nicotiana tabacum and P. fulva, respectively, while the family importance value index ranged from 0.2 for Annonaceae, Cupressaceae, Dracaenaceae, and Solanaceae to 41.6 for Araliaceae. Shannon and Simpson’s diversity indices were 1.772 and 0.707, respectively, while the evenness was 0.532, signifying that the forest was reasonably diverse. It is recommended that this forest can be conserved owing to its rich vegetation and to monitor its successional development.
Suitability of Different Diagnostic Platforms for Virological Testing of Blood Samples from Cornea Donors
Authors: Kohmer Niko , Kortenbusch Marhild , Berger Annemarie , Rühl Cornelia , Ciesek Sandra , Salla Sabine , Rabenau Holger F.
Published: June 2022

Background: To minimize the risk of disease transmission in cornea transplantation, donor screening for blood-derived viral infections is mandatory. Ideally, pre-mortem blood samples are used, but based on availability, cadaveric blood samples of cornea donors may also be used. However, serological and nucleic acid amplification tests (NATs) need to be validated for the use of cadaveric specimens. Methods: Hepatitis B virus (HBV), hepatitis C virus (HCV), human immunodeficiency virus (HIV), human T-lymphotropic virus (HTLV) 1/2, and Treponema pallidum (syphilis)-specific serological and/or NAT assays were validated on different platforms (Abbott Alinity i, Alinity m, Roche Cobas 6800, and Roche Cobas AmpliPrep/Cobas TaqMan (CAP/CTM)) using (un)spiked paired pre- and post-mortem cornea donor blood samples from the same individual (up to 23.83 h after death) of 28 individuals in accordance with the specifications of the German Federal Institute for Vaccines and Biomedicines (Paul-Ehrlich-Institut [PEI]). In addition, routinely HBV-, HCV- and HIV-PCR-negative tested post-mortem blood samples of 24 individuals were used to assess NAT specificity. Results: For the majority of serological parameters on the Abbott Alinity i (HBsAg, anti-HBc, anti-HBs, anti-HCV, anti-HIV, anti-HTLV 1/2, and anti-Treponema pallidum), ratios of generated test results of (un)spiked paired pre- and post-mortem blood samples differed ≤25%, with an agreement of qualitative pre- and post-mortem test results ranging from 91.2 to 100%. For NAT parameters (HBV, HCV, and HIV) on the Cobas 6800, Alinity m, and CAP/CTM, no significant deviation in virus concentrations (factor >5) of spiked pre- and post-mortem blood samples could be observed. Ct-values of corresponding internal controls did also not differ significantly (>1.5 Ct-values). In addition, no false-positive test results were generated when specificity was assessed. Conclusion: Overall, fluctuations of test results for serological and NAT parameters in pre- and post-mortem blood samples examined in this study, were only limited and within the range of what is also observed when routinely testing fresh patient specimens. We conclude that all examined assays are eligible for the screening of blood samples taken up to about 24 h after the occurrence of death.
Paraneoplastic Demyelinating Inflammatory Neuropathy Revealing Metastatic Seminoma: A Case Report
Authors: Cherifi François , Dereeper Olivier , Forestier Alexandra , Joly Florence , Penel Nicolas
Published: June 2022

Paraneoplastic neurological syndrome (PNS) is uncommon and not well known. PNS can reveal cancer, but its role in seminomas has not been described explicitly. We report the case of a 36-year-old man with unremarkable medical history and no comorbidities who was diagnosed with a retroperitoneal metastatic seminoma. The patient’s general condition deteriorated, and he developed progressive neurological palsy without other clinical anomalies. Electromyography revealed demyelinating, non-lengthy neuropathy. Guillain-Barré syndrome was initially suspected. However, a positron emission tomography scan revealed a retroperitoneal mass, and blood markers revealed increased human chorionic gonadotropin. The patient was diagnosed with PNS, and a computed tomography-guided biopsy revealed a metastatic seminoma without a primary tumor. No circulating neural antibodies were detected. Human polyvalent immunoglobulin was simultaneously administered with chemotherapy. After three cycles of a cisplatin-etoposide-bleomycin, a complete biological and metabolic response rate was observed, and his neurological symptoms rapidly improved. Four years later, the patient responded completely, without any neurological complaints. Paraneoplastic demyelinating inflammatory neuropathy can lead to advanced seminoma diagnosis. Prompt management of seminomas with cisplatin-based regimens provides the best chance of cure for both advanced seminoma and paraneoplastic syndrome.
A Systematic Review for Evaluation of Specialized Programs for Addressing Young Women with Breast Cancer Problems
Authors: Abedian Kasgri Kobra , Abazari Morteza , Tehrani Hadi , Yazdani Charati Jamshid , Momeni Badeleh Safa , Momeni Badeleh Kosar , Mahdizadeh Mehrsadat , Peyman Nooshin
Published: June 2022

Introduction: Breast cancer (BC) is one of the most common health concerns among women and is the leading cause of cancer-related death around the world. Women, in particular young women, face unique and complex problems with BC. Physical, psychological, emotional, educational, and long-term BC-related problems have been recognized for these vulnerable populations. Besides BC patients, their families and relatives challenge with various problems such as financial and supportive issues in supporting these patients. Methods: The main objective of the present study was to evaluate the BC patient’s major problems and describe current supportive initiatives and programs that support these patients, their advancements to date, existing challenges, and possible future actions. Data collection took place by conducting a comprehensive search on the Internet, Medline, PubMed, and Google Scholar databases. We also discuss the contingency options, which lead to improving medical and supportive care, as well as overcoming barriers to providing comprehensive and optimal care and support for these unique groups of patients. Results: The result revealed that several comprehensive and well-developed BC programs and initiatives have been established around the world for providing and focusing on BC patient’s clinical care, supportive care, education, survivorship, navigation, and research. However, despite considerable advancement in this area, there are still significant challenges in addressing the BC patient’s needs. Conclusion: Evaluation of the current situation of BC patient’s treatment and quality of life highlighted the importance of developing and implementing the new and most efficient healthcare programs and protocols, as well as improving and optimizing the existing ones to improve and enhance the survival rate and quality of life of BC patients.