bluuebunny/crossref_metadata_2025 huggingface dataset:
An Integrated Process for Gearbox Design
Authors: Mehdi K. , Play D.
Published: March 2021

The design process of a mechanical product gathers generally different activities (conceptual study, mechanical analysis, drawing, documentation, manufacture and assembly). Many design systems based on traditional programming methods have been developed to assist the user to one or several of these activities. These programs suffer generally from the previously defined sequences, the inefficiency of the heuristic knowledge representation and the inaptitude of manipulation of symbolic informations. Thus, the success of such new design systems necessitates the combination of several types of knowledge (heuristic, symbolic, numeric, etc.). These knowledge are generally complementary and can come from different sources of knowledge. The state of the art is characterized therefore by the coupling or the integration of these sources of knowledge and to put them in a stand alone design system. This system also has to be opened to the integration and the acceptance of other sources of knowledge that will be able to be integrated later. This paper has for objective to show from a practical point of view the feasibility of a such integrated system with the example of an industrial gearbox design. This mechanical example is sufficiently complicated to be significant and to put in light the encountered advantages and difficulties. Results will be presented and the design methodology will be specifically discussed.
Knowledge-Based Mechanical Spring Design System
Authors: Tai K. K. , Lin Yuyi , Wang L. X.
Published: March 2021

Expert systems are best known for qualitative or heuristic reasoning capability. However, the design of high performance and critical mechanical components, such as automotive valve springs, requires that precise and quantitative issues be resolved. This paper discusses the extended use of an expert system shell for mechanical spring design automation. An expert system shell is utilized as a user friendly front end and a binding agent among system components. Building blocks of the complete system include a product information data base which is provided by commercial manufacturers, a dynamic modeling and simulation module which includes typical-applications models, an optimization module which uses simulated annealing algorithms, and a design specification generation module which produces production drawings and a design report. The basic methodology discussed in this paper can be applied to the design automation of other mechanical components.
The Significance of Specifications in the Product Development Processes
Authors: Ahrens Gritt , Tegel Oliver
Published: March 2021

An approach to support the appropriate definition, formulation and presentation of requirements obeying the needs of the employees is being presented. Classifiying the needs for information of the employees according to some characteristics, a guideline for how to promote the information needed by them can be developed. The goal is to ensure that everyone involved in the process — even the subcontractor — has the right information available in the right form at the right time. Defining requirements lists, splitting them into partial requirements lists for each area of the company, each process phase or each team, and then formulating these requirements and presenting them in an adequate way is the proceeding strived for. The result will be implemented into an information infrastructure to support the product development process continuously.
Production and Classification-Based Active Structural Design Databases
Authors: Xirouchakis Paul C.
Published: March 2021

We consider the beam section design problem domain and its representation using the LOOM knowledge representation and reasoning database system. We use LOOM’s concept classification capabilities to built a taxonomy of terms describing the beam section design process. This allows LOOM to automatically classify concepts and instances of objects in the proper location in the taxonomy of terms. This classification-based reasoning is what distinguishes LOOM from other knowledge or object-oriented database systems. We also use LOOM’s two behavioral programming features: object-oriented and rule-based in our beam problem domain. This way we define the beam concepts of flat bar, exactly one flange, exactly two flanges and box type. We also define three versions of a section area calculation method that fires depending on the type of the beam section. Finally, we define a production that fires when the type of an object changes to tank boundary. As a result the applicable beam design pressure is changed accordingly.
Enterprise Modeling: Practices and Perspectives
Authors: Christensen Lars C. , Johansen Brage W. , Midjo Nils , Onarheim Jan , Syvertsen Tor G. , Totland Terje
Published: March 2021

This paper presents an overview of various approaches to enterprise modeling, illustrated by present and future applications of enterprise modeling technology. A taxonomy derived from different objectives of enterprise modeling is proposed.

Preliminary experiences from a large-scale enterprise modeling and organizational restructuring project are reported. The project was conducted at a natural gas process plant operated by the Norwegian oil company Statoil.

We argue that the potential of enterprise modeling in business process improvements only can be utilized when the methodology is brought to the heads and hands of the inhabitants of the enterprise.

Finally, a coordination environment denoted “the control room metaphor” is presented as a futuristic view of enterprise model development and application.
Constrained Structural Design Databases
Authors: Xirouchakis Paul C.
Published: March 2021

The technology of constrained databases (CDBs) is employed in the design of structural design databases. To illustrate the application of CDBs in structural design, the following example is considered in some detail: the design of a database for combined stiffener-plate sectional properties.

A major drawback of relational database technology (RDBs) for engineering applications is that constraints cannot be processed within the data model. Another major drawback of the relational data model for engineering applications is that it only can incorporate attributes with discrete value set i.e. it cannot represent effectively variables with a continuous range.

To remedy this situation, we propose the use of CDBs which are extended RDBs (so that they retain the advantages of RDBs) that can process arithmetic constraints in both relations and queries. CDBs can represent infinite point sets through the respective constraints on variables with a continuous range.

We provide the database schema specification and specification for a number of typical queries for the example problem of combined stiffener-plate sectional properties database. We also specify constraints in the data models that model structural stability and manufacturing constraints.
Tree frog-inspired nanopillar arrays for enhancement of adhesion and friction
Authors: Shi Zhekun , Tan Di , Liu Quan , Meng Fandong , Zhu Bo , Xue Longjian
Published: March 2021

Bioinspired structure adhesives have received increasing interest for many applications, such as climbing robots and medical devices. Inspired by the closely packed keratin nanopillars on the toe pads of tree frogs, tightly arranged polycaprolactone nanorod arrays are prepared by mold process and chemical modification. Nanorod arrays show enhanced adhesion and friction on both smooth and rough surfaces compared to the arrays with hexagonal micropillars. The bonding of nanorods results in a larger stiffness of the nanorod surface, contributing mainly to friction rather than adhesion. The results suggest the function of closely packed keratin nanopillars on the toe pad of tree frogs and offer a guiding principle for the designing of new structured adhesives with strong attaching abilities.
Sensitivity of the iLOAD® Application for Monitoring Changes in Barbell Velocity Following Power- and Strength-Oriented Resistance Training Programs
Authors: Pérez-Castilla Alejandro , Boullosa Daniel , García-Ramos Amador
Published: March 2021

Objective: To evaluate the sensitivity of the iLOAD® application to detect the changes in mean barbell velocity of complete sets following power- and strength-oriented resistance training (RT) programs. Methods: Twenty men were randomly assigned to a power training group (countermovement jump and bench press throw at 40% of the 1-repetition maximum [1RM]) or strength training group (back squat and bench press at 70% to 90% of 1RM). Single sets of 10 repetitions at 25% and 70% of 1RM during the back squat and bench press exercises were assessed before and after the 4-week RT programs simultaneously with the iLOAD® application and a linear velocity transducer. Results: The power training group showed a greater increment in velocity performance at the 25% of 1RM (effect size range = 0.66–1.53) and the 70% of 1RM (effect size range = 0.11–0.30). The percent change in mean velocity after the RT programs highly correlated between the iLOAD® application and the linear velocity transducer for the back squat (r range = .85–.88) and bench press (r range = .87–.93). However, the iLOAD® application revealed a 2% greater increase in mean velocity after training compared to the linear velocity transducer. Conclusions: The iLOAD® application is a cost-effective, portable, and easy-to-use tool which can be used to detect changes in mean barbell velocity after power- and strength-oriented RT programs.
Performance Analysis in Football-Specific Tests by Para-Footballers With Cerebral Palsy: Implications for Evidence-Based Classification
Authors: Yanci Javier , Castillo Daniel , Iturricastillo Aitor , Aracama Astrid , Roldan Alba , Reina Raúl
Published: March 2021

Purpose: The objectives of this study were to analyze whether there were differences among para-footballers with different types and degrees of brain impairment (ie, bilateral spasticity, athetosis/ataxia, unilateral spasticity, minimum impairment criteria, or no impairment) in performing 3 football-specific tests requiring ball dribbling, to analyze whether there was an association among the results obtained in the 3 tests, and to determine whether the performance in the tests was associated with competitive level, level of training, or years’ experience in para-footballers with cerebral palsy (CP). Methods: A total of 123 footballers took part in the study, 87 of whom were footballers with CP and 36 who were without impairment. Both groups were assessed in 3 football-specific tests (Stop and Go, Turning and Dribbling, and the Illinois Agility Test). Results: The results showed that the footballers without impairment recorded a better performance in all tests (P < .01) in comparison with the CP players. No significant differences in test performance were observed among the CP players from different competitive levels. However, significant differences (P < .01) were observed between players with diplegia or athetosis/ataxia compared with players with hemiplegia or minimum impairment level. Performance in the tests did not correlate with years of football experience, weekly strength training sessions, or specific football training in the footballers with CP (P = .12–.95). Conclusions: These findings suggest the possible inclusion of these tests in the classification process for footballers with CP because they discriminate among functional classes and are resistant to training and competitive level.
Not All About the Effort? A Comparison of Playing Intensities During Winning and Losing Game Quarters in Basketball
Authors: Fox Jordan L. , Green Jesse , Scanlan Aaron T.
Published: March 2021

Purpose: To compare peak and average intensities encountered during winning and losing game quarters in basketball players. Methods: Eight semiprofessional male basketball players (age = 23.1 [3.8] y) were monitored during all games (N = 18) over 1 competitive season. The average intensities attained in each quarter were determined using microsensors and heart-rate monitors to derive relative values (per minute) for the following variables: PlayerLoad, frequency of high-intensity and total accelerations, decelerations, changes of direction, jumps, and total inertial movement analysis events combined, as well as modified summated-heart-rate-zones workload. The peak intensities reached in each quarter were determined using microsensors and reported as PlayerLoad per minute over 15-second, 30-second, 1-minute, 2-minute, 3-minute, 4-minute, and 5-minute sample durations. Linear mixed models and effect sizes were used to compare intensity variables between winning and losing game quarters. Results: Nonsignificant (P > .05), unclear–small differences were evident between winning and losing game quarters in all variables. Conclusions: During winning and losing game quarters, peak and average intensities were similar. Consequently, factors other than the intensity of effort applied during games may underpin team success in individual game quarters and therefore warrant further investigation.
Volcanic carbon cycling in East Lake, Newberry Volcano, Oregon, USA
Authors: Brumberg H.D. , Capece L. , Cauley C.N. , Tartell P. , Smith C. , Wagner M.S. , Varekamp J.C.
Published: March 2021

The carbon cycle in East Lake (Newberry Volcano, Oregon, USA) is fueled by volcanic CO2 inputs with traces of Hg and H2S. The CO2 dissolves in deep lake waters and is removed in shallow waters through largely diffusive surface degassing and photosynthesis. Escaping gas and photosynthate have low δ13C values, leading to δ13C(DIC) (DIC—dissolved inorganic carbon) as high as +5.7‰ in surface waters, well above the common global lake range. A steep δ13C depth gradient is further established by respiration and absorption of light volcanic CO2 in bottom waters. The seasonal CO2 degassing starts at >100 t CO2/day after ice melting in the spring and declines to ∼40 t/day in late summer, degassing ∼11,700 t CO2/yr. Thus, volcano monitoring through gas fluxes from crater lakes should consider lacustrine processes that modulate the volcanic gas output over time. The flux contribution of a bubbling CO2 “hotspot” increased from 20% to >90% of the lake-wide CO2 flux from 2015 to 2019 CE, followed by a “toxic gas alert” in July 2020. East Lake is an active volcanic lake with a “geogenic” ecosystem driven primarily by hydrothermal inputs.
Supplemental Material: Isotopically “heavy” pyrite in marine sediments due to high sedimentation rates and non-steady-state deposition
Authors: Liu Jiarui , al. et
Published: March 2021

Supplemental methods, diagenetic model, Table S1, and Figures S1–S5.
Import of Palmer amaranth (Amaranthus palmeri S. Wats.) seed with sweet potato (Ipomoea batatas (L.) Lam) slips
Authors: Page Eric R. , Nurse Robert E. , Meloche Sydney , Bosveld Kerry , Grainger Christopher , Obeid Kristen , Filotas Melanie , Josée Simard Marie , Laforest Martin
Published: March 2021

Palmer amaranth is one of the most economically important and widespread weeds of arable land in the United States. Although no populations are currently known to exist in Canada, its distribution has expanded northward such that it is present in many of the states bordering Canada and multiple pathways exist for its introduction. In this short communication, we report on the transport of viable Palmer amaranth seed on imported sweet potato slips. A reproductive pair of Palmer amaranth seedlings were identified from soil accompanying imported sweet potato slips in 2018. Identification was confirmed using species-specific single nucleotide polymorphisms.
A Quasi-Normal Distribution and its Application in Parameter Estimation on Heavily Censored Data
Authors: Jiang Renyan
Published: March 2021

Parameter estimation on heavily censored data is a challenging issue. This paper addresses this issue using a two-step single-parameter maximum likelihood method to estimate mean time to failure (MTTF) and Weibull shape parameter (WSP). The first step fits the data to three one-parameter auxiliary models, which are special cases of a two-parameter quasi-normal distribution with nonnegative support, to obtain three estimates of the MTTF. The second step estimates the WSP through fixing each of the MTTF estimates. The best estimates are selected from three pairs of estimates based on appropriate rules. A simple numerical method is also proposed to construct the confidence intervals of the estimated MTTF and WSP. The auxiliary models are derived, the model selection rules are specified, and a numerical experiment is carried out to illustrate the accuracy of the proposed method.
A Markovian Control Approach to Maintenance Optimization of a System with Stochastic Dependence and Hidden Failures
Authors: Ahmadi Reza
Published: March 2021

Given partial information, this paper considers both disruption and maintenance scheduling problem for a parallel-series system with failure interactions and hidden failures. By projection on an observed history, the filtering treatment contributes to detecting an unobservable disruption time at which one of subsystems experiences failure. The model is developed by setting it in a Markovian control framework with partial information pattern in which a control process as a repair level impacts on the system availability via maintaining both the inspection and the disruption intensity at a desirable level. Since each repair and maintenance action incurs cost, the problem is to determine an optimal control process that balances the amount of maintenance and maintenance costs. The optimal control process emerges as the solution of deterministic Hamilton Jacobi equations, and a recursive scheme is used to solve them. We illustrate the procedure for the case when the failure time of components is defined as the first passage time of a Wiener process. The proposed model is illustrated through numerical examples.
An elementary approach to subdiffusion
Authors: Floriani Elena , Lima Ricardo , Ugalde Edgardo
Published: March 2021

We consider a basic one-dimensional model which allows to obtain a diversity of diffusive regimes whose speed depends on the moments of a per-site trapping time. This models a discrete subordinated random walk, closely related to the continuous time random walks widely studied in the literature. The model we consider lends itself to a detailed elementary treatment, based on the study of recurrence relation for the time-[Formula: see text] dispersion of the process, making it possible to study deviations from normality due to finite time effects.
Developmental Insights into Lung Cancer
Authors: Desai Tushar J.
Published: March 2021

Lung cancer continues to be the number one cancer killer. Despite a surge of therapeutic advances in recent years, lung cancer remains fatal when it presents at a stage too advanced for surgical resection. In part, this is due to the disappointing reality of inevitable drug resistance in the face of highly effective, mutation-specific chemotherapy and the limited efficacy of immune checkpoint blockade. Yet, with the increasing application and integration of diverse genomic profiling approaches and the advent of high-content single-cell technologies, the mechanisms of lung cancer initiation, evolution, spread, and resistance are being unraveled at unprecedented resolution. Increasingly sophisticated mouse genetic, xenotransplantation, and ex vivo assays are also enabling functional validation and empiric screening of new therapeutic candidates. In this review, I highlight recent insights into the genetic, cellular, and molecular mechanisms of lung cancer and relate them to the normal biology of the developing and mature lung.
Relating human physiology content to COVID-19: a strategy to keep students in touch with physiology in times of social distance due to pandemic
Authors: Alves Niege , Carrazoni Guilherme Salgado , Soares Caroline Bitencourt , Rosa Ana Carolina de Souza da , Soares Náthaly Marks , Mello-Carpes Pâmela Billig
Published: March 2021

In 2020 universities had to quickly implement remote education alternatives as a result of the social distancing due to the COVID-19 pandemic. To keep students engaged with the university, we implemented a teaching-learning model that relates physiology contents to the COVID-19 pandemic using online educational platforms. A 1-mo web course was proposed for health sciences students from the Federal University of Pampa. It included synchronous meetings twice a week and asynchronous activities using scientific articles, case studies, and interactive online tools. The students approved the methodology developed, assessing it as dynamic and innovative. They reported that the activity helped to better understand the relations between COVID-19 and physiological systems. The web course also contributed to the identification of reliable sources of news and stimulated the sharing of scientific content with their families. We concluded that the use of online platforms contextualizing the physiology content considering current events helps students in learning human physiology and improves their abilities to apply this information to their daily life, in this specific case, regarding the COVID-19 pandemic.
Nasal respiratory support and tachypnea and oral feeding in full-term newborn lambs
Authors: Alain Charles , Samson Nathalie , Nadeau Charlène , Beaudoin Jean-François , Lienhart Camille , Counil Clément , Praud Jean-Paul
Published: March 2021

The practice of orally feeding newborns suffering from respiratory problems while on nCPAP or HFNC remains controversial for fear of triggering cardiorespiratory events or aspiration pneumonia, or aggravating chronic lung disease. The present results show that bottle-feeding is generally safe in full-term lambs under nasal respiratory support, both without and with tachypnea.
Longitudinal Joint Modelling of Ordinal and Overdispersed Count Outcomes: A Bridge Distribution for the Ordinal Random Intercept
Authors: Amini Payam , Moghimbeigi Abbas , Zayeri Farid , Tapak Leili , Maroufizadeh Saman , Verbeke Geert
Published: March 2021

Associated longitudinal response variables are faced with variations caused by repeated measurements over time along with the association between the responses. To model a longitudinal ordinal outcome using generalized linear mixed models, integrating over a normally distributed random intercept in the proportional odds ordinal logistic regression does not yield a closed form. In this paper, we combined a longitudinal count and an ordinal response variable with Bridge distribution for the random intercept in the ordinal logistic regression submodel. We compared the results to that of a normal distribution. The two associated response variables are combined using correlated random intercepts. The random intercept in the count outcome submodel follows a normal distribution. The random intercept in the ordinal outcome submodel follows Bridge distribution. The estimations were carried out using a likelihood-based approach in direct and conditional joint modelling approaches. To illustrate the performance of the model, a simulation study was conducted. Based on the simulation results, assuming a Bridge distribution for the random intercept of ordinal logistic regression results in accurate estimation even if the random intercept is normally distributed. Moreover, considering the association between longitudinal count and ordinal responses resulted in estimation with lower standard error in comparison to univariate analysis. In addition to the same interpretation for the parameter in marginal and conditional estimates thanks to the assumption of a Bridge distribution for the random intercept of ordinal logistic regression, more efficient estimates were found compared to that of normal distribution.
Global Attractor for Second‐Order Nonlinear Evolution Differential Inclusions
Authors: Su Guangwang , Lin Funing
Published: March 2021

In this paper, we address the model of global attractor formulated in the form of evolution differential inclusions with second order in Banach spaces. Firstly, based on the fixed point theorem, the existence result of mild solutions is deduced. Then, by implementing the measure of noncompactness, the existence of global attractor associated with m‐semiflow is validated. Finally, a concrete application of the main result is demonstrated to enhance the practical signification.
Melatonin Attenuates ox‐LDL‐Induced Endothelial Dysfunction by Reducing ER Stress and Inhibiting JNK/Mff Signaling
Authors: Li Peng , Xie Changlian , Zhong Jiankai , Guo Zhongzhou , Guo Kai , Tu Qiuyun
Published: March 2021

Endothelial dysfunction, which is characterized by damage to the endoplasmic reticulum (ER) and mitochondria, is involved in a variety of cardiovascular disorders. Here, we explored whether mitochondrial damage and ER stress are associated with endothelial dysfunction. We also examined whether and how melatonin protects against oxidized low‐density lipoprotein‐ (ox‐LDL‐) induced damage in endothelial cells. We found that CHOP, GRP78, and PERK expressions, which are indicative of ER stress, increased significantly in response to ox‐LDL treatment. ox‐LDL also induced mitochondrial dysfunction as evidenced by decreased mitochondrial membrane potential, increased mitochondrial ROS levels, and downregulation of mitochondrial protective factors. In addition, ox‐LDL inhibited antioxidative processes, as evidenced by decreased antioxidative enzyme activity and reduced Nrf2/HO‐1 expression. Melatonin clearly reduced ER stress and promoted mitochondrial function and antioxidative processes in the presence of ox‐LDL. Molecular investigation revealed that ox‐LDL activated the JNK/Mff signaling pathway, and melatonin blocked this effect. These results demonstrate that ox‐LDL induces ER stress and mitochondrial dysfunction and activates the JNK/Mff signaling pathway, thereby contributing to endothelial dysfunction. Moreover, melatonin inhibited JNK/Mff signaling and sustained ER homeostasis and mitochondrial function, thereby protecting endothelial cells against ox‐LDL‐induced damage.
A Clinical Study on the Treatment of Multiple Radial Fractures with Embedded Wearable Device Holder and Absorption Bone Nail Combined with Decoction
Authors: Ren Zhilong , Li Xiangyang
Published: March 2021

Multiple radial fractures have brought great pain to the patients, and the treatment takes a long time and the effect is slow, which seriously affects people’s production and life. Traditional conservative treatment methods are mostly used for radius fractures. However, with the development of science and technology of the times, the level of medical treatment is also constantly improving. For radius fractures, the embedded wearable device fixation frame absorption bone nail treatment method has attracted attention. In order to study whether the embedded wearable device fixation frame can treat radius fractures, this article conducted a related survey of radius fracture patients in a hospital in a certain city, reviewed related literature, conducted interviews with professionals and so forth, and collected relevant information. A case template was constructed, and a clinical research model was created using a comprehensive quantitative and qualitative analysis method. The results of the study found that using the research embedded wearable device fixation frame to treat radius fractures with absorption bone nails can achieve good results, and its healing efficiency is about 20% faster than conservative treatment. With decoction, its treatment efficiency can be improved; and the prognostic treatment of the decoction can reduce the complications of the patient’s treatment by about 13%. This shows that the embedded wearable device holder absorption bone nail combined with decoction can play an important role in the treatment of multiple radius fractures.
Positive Effect of Electroacupuncture Treatment on Gut Motility in Constipated Mice Is Related to Rebalancing the Gut Microbiota
Authors: Xu Mingmin , Wang Lu , Guo Yu , Zhang Wei , Chen Ying , Li Ying
Published: March 2021

Functional constipation (FC) is a common and often recurrent functional bowel disorder that seriously affects the quality of life of affected individuals and incurs a significant economic burden on both the individual and society. There is accumulating evidence that intestinal dysbiosis contributes to constipation and that rebalancing the gut microbiota may be a novel therapeutic modality for FC. Electroacupuncture (EA) has been shown to restore the gut microbiota to normal levels in a variety of diseases. Additionally, several high-quality clinical studies have confirmed that EA is an effective, sustained, and safe treatment for FC. However, whether the effects of EA are secondary to changes in the gut microbiota and how EA modulates intestinal dysbiosis induced by constipation are unknown. Therefore, here, we focused on the potential regulatory mechanisms of EA on diphenoxylate-induced constipation in mice by analyzing structural changes in the gut microbiota. Our results showed that EA treatment effectively rebalanced the gut microbiota of constipated mice, mainly by decreasing the Firmicutes/Bacteroidetes ratio, which may represent one way in which EA promotes gastrointestinal motility and alleviates constipation. Our findings lay the foundation for further mechanistic and clinical research into the application of EA in patients with FC.
High Carriage Rate of Extended-Spectrum β-Lactamase-Producing Escherichia coli and Klebsiella Species among Poultry Meat Vendors in Dar es Salaam: The Urgent Need for Intervention to Prevent the Spread of Multidrug-Resistant Pathogens
Authors: Mwanginde Lutengano W. , Majigo Mtebe , Kajeguka Debora C. , Joachim Agricola
Published: March 2021

Background. Bacteria possessing extended-spectrum beta-lactamase (ESBL), especially E. coli and Klebsiella species, are problematic, particularly in hospitalized patients. Poultry meat vendors are at risk of carrying ESBL-producing bacteria when processing and handling meat products in an unhygienic environment. There is limited information on the carriage rate of ESBL-producing pathogens among poultry meat vendors that necessitated the conduction of the study. Method. A cross-sectional study was conducted among poultry meat vendors in Dar es Salaam, Tanzania. Participants provided rectal swabs in transport media upon instruction. The primary isolation of ESBL-producing bacteria was carried out using MacConkey agar supplemented with ceftazidime. Identification of isolates relied on conventional methods. Double-disk synergy was the method used to confirm ESBL-producing isolates. We performed descriptive statistics using Statistical Package for Social Sciences version 23. A

p

value < 0.05 was considered statistically significant. Results. A total of 300 participants were recruited from five districts, with a mean age of 27.2 ± 6.7 years. The majority was male (67.3%), and 74.7% worked as poultry meat vendors for more than one year. Out of 300 participants, 107 (35.7%) had confirmed ESBL-producing E. coli and Klebsiella spp. The majority of confirmed ESBL-producing isolates was E. coli (78.5%). Participants from Ubungo District had significantly higher carriage of ESBL-producing Escherichia coli and Klebsiella spp. (48.0%, 95% CI: 34.8–47.7) than Temeke District (21.4%, 95% CI: 13.4–32.4). Only 28.0% of participants had access to latrines at the workplace, and all working areas lacked access to running water. Conclusion. The study revealed a relatively high fecal carriage rate of ESBL-producing E. coli and Klebsiella spp. among poultry meat vendors. Poor working environments and hygienic practices are risks for spread of these multidrug-resitant pathogens.
A Blockchain System Based on Quantum-Resistant Digital Signature
Authors: Zhang Peijun , Wang Lianhai , Wang Wei , Fu Kunlun , Wang Jinpeng
Published: March 2021

Blockchain, which has a distributed structure, has been widely used in many areas. Especially in the area of smart cities, blockchain technology shows great potential. The security issues of blockchain affect the construction of smart cities to varying degrees. With the rapid development of quantum computation, elliptic curves cryptosystems used in blockchain are not secure enough. This paper presents a blockchain system based on lattice cipher, which can resist the attack of quantum computation. The most challenge is that the size of public keys and signatures used by lattice cryptosystems is typically very large. As a result, each block in a blockchain can only accommodate a small number of transactions. It will affect the running speed and performance of the blockchain. For overcoming this problem, we proposed a way that we only put the hash values of public keys and signatures on the blockchain and store the complete content of them on an IPFS (interplanetary file system). In this way, the number of bytes occupied by each transaction is greatly reduced. We design a bitcoin exchange scheme to evaluate the performance of the proposed quantum-resistant blockchain system. The simulation platform is verified to be available and effective.
Machine Learning‐Based Modeling with Optimization Algorithm for Predicting Mechanical Properties of Sustainable Concrete
Authors: Shah Muhammad Izhar , Memon Shazim Ali , Khan Niazi Muhammad Sohaib , Amin Muhammad Nasir , Aslam Fahid , Javed Muhammad Faisal
Published: March 2021

In this research, multiexpression programming (MEP) has been employed to model the compressive strength, splitting tensile strength, and flexural strength of waste sugarcane bagasse ash (SCBA) concrete. Particle swarm optimization (PSO) algorithm was used to fine‐tune the hyperparameter of the proposed MEP. The formulation of SCBA concrete was correlated with five input parameters. To train and test the proposed model, a large number of data were collected from the published literature. Afterward, waste SCBA was collected, processed, and characterized for partial replacement of cement in concrete. Concrete specimens with varying proportion of SCBA were prepared in the laboratory, and results were used for model validation. The performance of the developed models was then evaluated by statistical criteria and error assessment tests. The result shows that the performance of MEP with PSO algorithm significantly enhanced its accuracy. The essential input variables affecting the output were revealed, and the parametric analysis confirms that the models are accurate and have captured the essential properties of SCBA. Finally, the cross validation ensured the generalized capacity and robustness of the models. Hence, the adopted approach, i.e., MEP‐based modeling with PSO, could be an effective tool for accurate modeling of the concrete properties, thus directly contributing to the construction sector by consuming waste and protecting the environment.
Uncovering the Role of Oxidative Imbalance in the Development and Progression of Bronchial Asthma
Authors: Vasconcelos Luiz H. C. , Ferreira Sarah R. D. , Silva Maria da C. C. , Ferreira Paula B. , Souza Iara L. L. de , Cavalcante Fabiana de A. , Silva Bagnólia A. da
Published: March 2021

Asthma is a chronic inflammatory disease of the airways related to epithelial damage, bronchial hyperresponsiveness to contractile agents, tissue remodeling, and luminal narrowing. Currently, there are many data about the pathophysiology of asthma; however, a new aspect has emerged related to the influence of reactive oxygen and nitrogen species (ROS and RNS) on the origin of this disease. Several studies have shown that an imbalance between the production of ROS and RNS and the antioxidant enzymatic and nonenzymatic systems plays an important role in the pathogenesis of this disease. Considering this aspect, this study is aimed at gathering data from the scientific literature on the role of oxidative distress in the development of inflammatory airway and lung diseases, especially bronchial asthma. For that, articles related to these themes were selected from scientific databases, including human and animal studies. The main findings of this work showed that the respiratory system works as a highly propitious place for the formation of ROS and RNS, especially superoxide anion, hydrogen peroxide, and peroxynitrite, and the epithelial damage is reflected in an important loss of antioxidant defenses that, in turn, culminates in an imbalance and formation of inflammatory and contractile mediators, such as isoprostanes, changes in the activity of protein kinases, and activation of cell proliferation signalling pathways, such as the MAP kinase pathway. Thus, the oxidative imbalance appears as a promising path for future investigations as a therapeutic target for the treatment of asthmatic patients, especially those resistant to currently available therapies.
[Retracted] Human Posture Recognition and Estimation Method Based on 3D Multiview Basketball Sports Dataset
Authors: Song Xuhui , Fan Linyuan
Published: March 2021

In traditional 3D reconstruction methods, using a single view to predict the 3D structure of an object is a very difficult task. This research mainly discusses human pose recognition and estimation based on 3D multiview basketball sports dataset. The convolutional neural network framework used in this research is VGG11, and the basketball dataset Image Net is used for pretraining. This research uses some modules of the VGG11 network. For different feature fusion methods, different modules of the VGG11 network are used as the feature extraction network. In order to be efficient in computing and processing, the multilayer perceptron in the network model is implemented by a one‐dimensional convolutional network. The input is a randomly sampled point set, and after a layer of perceptron, it outputs a feature set of n × 16. Then, the feature set is sent to two network branches, one is to continue to use the perceptron method to generate the feature set of n × 1024, and the other network is used to extract the local features of points. After the RGB basketball sports picture passes through the semantic segmentation network, a picture containing the target object is obtained, and the picture is input to the constructed feature fusion network model. After feature extraction is performed on the RGB image and the depth image, respectively, the RGB feature, the local feature of the point cloud, and the global feature are spliced and fused to form a feature vector of N × 1152. There are three branches for this vector network, which, respectively, predict the object position, rotation, and confidence. Among them, the feature dimensionality reduction is realized by one‐dimensional convolution, and the activation function is the ReLU function. After removing the feature mapping module, the accuracy of VC‐CNN_v1 dropped by 0.33% and the accuracy of VC‐CNN_v2 dropped by 0.55%. It can be seen from the research results that the addition of the feature mapping module improves the recognition effect of the network to a certain extent
Convolutional Neural Network‐Based Discriminator for Outlier Detection
Authors: Alharbi Fahad , El Hindi Khalil , Al Ahmadi Saad , Alsalamn Hussien
Published: March 2021

Noise in training data increases the tendency of many machine learning methods to overfit the training data, which undermines the performance. Outliers occur in big data as a result of various factors, including human errors. In this work, we present a novel discriminator model for the identification of outliers in the training data. We propose a systematic approach for creating training datasets to train the discriminator based on a small number of genuine instances (trusted data). The noise discriminator is a convolutional neural network (CNN). We evaluate the discriminator’s performance using several benchmark datasets and with different noise ratios. We inserted random noise in each dataset and trained discriminators to clean them. Different discriminators were trained using different numbers of genuine instances with and without data augmentation. We compare the performance of the proposed noise‐discriminator method with seven other methods proposed in the literature using several benchmark datasets. Our empirical results indicate that the proposed method is very competitive to the other methods. It actually outperforms them for pair noise.
Semantic-Segmentation-Based Rail Fastener State Recognition Algorithm
Authors: Li Liming , Sun Rui , Zhao Shuguang , Chai Xiaodong , Zheng Shubin , Shen Ruichao
Published: March 2021

Rail fastener status recognition and detection are key steps in the inspection of the rail area status and function of real engineering projects. With the development of and widespread interest in image processing techniques and deep learning theory, detection methods that combine the two have yielded promising results in practical detection applications. In this paper, a semantic-segmentation-based algorithm for the state recognition of rail fasteners is proposed. On the one hand, we propose a functional area location and annotation method based on a salient detection model and construct a novel slab-fastclip-type rail fastener dataset. On the other hand, we propose a semantic-segmentation-framework-based model for rail fastener detection, where we detect and classify rail fastener states by combining the pyramid scene analysis network (PSPNet) and vector geometry measurements. Experimental results prove the validity and superiority of the proposed method, which can be introduced into practical engineering projects.
A 3-dimensional fast machine learning algorithm for mobile unmanned aerial vehicle base stations
Authors: Shafik Wasswa , Matinkhah S. Motjaba , Afolabi Solagbade Saheed , Sanda Mamman Nur
Published: March 2021

The 5G technology is predicted to achieve the unoptimized millimeter Wave (mmWave) of 30-300 GHz bands. This unoptimized band because of the loss of mm-Wave bands, like path attenuation and propagation losses. Nonetheless, because of: (i) directional transmission paving way for beamforming to recompense for the path attenuation, and (ii) sophisticated placement concreteness of the base stations (BS) is the best alternative for array wireless communications in mmWave bands (that is to say 100-150 m). The advance in technology and innovation of unmanned aerial vehicles (UAVs) necessitates many opportunities and uncertainties. UAVs are agile and can fly all complexities if the terrains making ground robots unsuitable. The UAV may be managed either independently through aboard computers or distant controlled of a flight attendant on pulverized wireless communication links in our case 5G. Although a fast algorithm solved the problematic aspect of beam selection for 2-dimensional scenarios. This paper presents 3-dimensional scenarios for UAV. We modeled beam selection with environmental responsiveness in millimeter Wave UAV to accomplish close optimum assessments on the regular period through learning from the available situation.
Future trends in mechatronics
Authors: Nnodim Chiebuka T. , Arowolo Micheal O. , Agboola Blessing D. , Ogundokun Roseline O. , Abiodun Moses K.
Published: March 2021

Presently, the move towards a more complex and multidisciplinary system development is increasingly important in order to understand and strengthen engineering approaches for the systems in the engineering field. This will lead to the effective and successful management of these systems. The scientific developments in computer engineering, simulation and modeling, electromechanical motion tools, power electronics, computers and informatics, micro-electro-mechanical systems (MEMS), microprocessors, and distributed system platforms (DSPs) have brought new challenges to industry and academia. Important aspects of designing advanced mechatronic products include modeling, simulation, analysis, virtual prototyping, and visualization. Competition on a global market includes the adaptation of new technology to produce better, cheaper, and smarter, scalable, multifunctional goods. Since the application area for developing such systems is very broad, including, for example, automotive, aeronautics, robotics or consumer products, and much more, there is also the need for flexible and adaptable methods to develop such systems. These dynamic interdisciplinary systems are called mechatronic systems, which refer to a system that possess synergistic integration of Software, electronic, and mechanical systems. To approach the complexity inherent in the aspects of the discipline, different methods and techniques of development and integration are coming from the disciplines involved. This paper will provide a brief review of the history, current developments and the future trends of mechatronics in general view.
Association of Epicardial Fat Volume With Increased Risk of Obstructive Coronary Artery Disease in Chinese Patients With Suspected Coronary Artery Disease
Authors: Yu Wenji , Liu Bao , Zhang Feifei , Wang Jianfeng , Shao Xiaoliang , Yang Xiaoyu , Shi Yunmei , Wang Bing , Xu Yiduo , Wang Yuetao
Published: March 2021

Background

Epicardial adipose tissue may be associated with the pathogenesis of coronary artery disease (CAD), but its effect on obstructive CAD risk is uncertain. Therefore, we aimed to examine the relationship between epicardial adipose tissue and obstructive CAD in Chinese patients with suspected CAD.

Methods and Results

The present study enrolled 194 consecutive inpatients with suspected CAD who underwent both noncontrast computed tomography and coronary angiography. We measured epicardial fat volume (EFV) and evaluated its association with obstructive CAD, which was defined as coronary stenosis severity ≥70%. Overall, 44.3% patients had obstructive CAD and tend to have higher EFV. Age, body mass index, triglycerides, incidence of hypertension, and hyperlipidemia were higher across tertiles of EFV (
P
for trend <0.05). In univariate regression analysis, a per‐SD increase in EFV was independently associated with obstructive CAD (odds ratio [OR], 2.31; 95% CI, 1.61–3.32;
P
<0.001). Consistent with these findings, EFV was still significantly related to obstructive CAD as continuous variable after adjustment for all traditional risk factors and coronary artery calcium (OR per SD, 2.82; 95% CI, 1.68–4.74;
P
<0.001). Generalized additive model indicated that EFV was linearly associated with risk of obstructive CAD.
E
‐value analysis suggested robustness to unmeasured confounding.

Conclusions

Our results suggested that in Chinese patients with suspected CAD, EFV was significantly and positively associated with the risk of obstructive CAD, independent of traditional risk factors and coronary artery calcium.