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Many studies have been conducted on measuring avian influenza viruses and their hemagglutinin (HA) antigens via electrochemical principles; most of these studies have used gold electrodes on ceramic, glass, or silicon substrates, and/or labeling for signal enhancement. Herein, we present a paper-based immunosensor for label-free measurement of multiple avian influenza virus (H5N1, H7N9, and H9N2) antigens using flexible screen-printed carbon nanotube-polydimethylsiloxane electrodes. These flexible electrodes on a paper substrate can complement the physical weakness of the paper-based sensors when wetted, without affecting flexibility. The relative standard deviation of the peak currents was 1.88% when the electrodes were repeatedly bent and unfolded twenty times with deionized water provided each cycle, showing the stability of the electrodes. For the detection of HA antigens, approximately 10-μl samples (concentration: 100 pg/ml–100 ng/ml) were needed to form the antigen–antibody complexes during 20–30 min incubation, and the immune responses were measured via differential pulse voltammetry. The limits of detections were 55.7 pg/ml (0.95 pM) for H5N1 HA, 99.6 pg/ml (1.69 pM) for H7N9 HA, and 54.0 pg/ml (0.72 pM) for H9N2 HA antigens in phosphate buffered saline, and the sensors showed good selectivity and reproducibility. Such paper-based sensors are economical, flexible, robust, and easy-to-manufacture, with the ability to detect several avian influenza viruses.

The wettability of the paper surface is greatly affected by the wettability of the pulp fibers. We conducted this study in order to understand the relationship between the wettability of a single fiber of recycled pulp and the strength of recycled paper, as well as the inter-fiber bonding strength. The contact angle was determined from a series of photographs of the pulp fiber and the water silhouettes at the point of contact. The contact line and profile history were continuously photographed in every 1 s after the initial contact. The recycled softwood kraft pulp fibers were clearly much less hydrophilic than the original fibers, regardless of whether the fibers had been bleached or not. The contact angle of the original chemi-thermomechanical pulp fiber was much higher than that of the original softwood bleached kraft pulp fiber. Furthermore, increased number of recycling decreased the contact angle of the chemi-thermomechanical pulp fiber. The Page equation was used to evaluate the strength contributions of single fiber and fiber–fiber bonding to tensile strength of paper. As a result, an increase in weakness factor of fiber–fiber bonding strength was obtained for the recycled softwood kraft pulp handsheet. On the other hand, the weakness factor of the original chemi-thermomechanical pulp handsheet decreased with recycling. In addition, the weakness factor of fiber–fiber bonding strength and the contact angles of the provided softwood bleached kraft pulp fibers bore a proportional relationship to each other.

Three-dimensional visualization of cellular and subcellular-structures in histological-tissues is essential for understanding the complexities of biological-phenomena, especially with regards structural and spatial relationships and pathologlical-diagnosis. Recent advancements in tissue-clearing technology, such as Magnified Analysis of Proteome (MAP), have significantly improved our ability to study biological-structures in three-dimensional space; however, their wide applicability to a variety of tissues is limited by long incubation-times and a need for advanced imaging-systems that are not readily available in most-laboratories. Here, we present optimized MAP-based method for paper-thin samples, Paper-MAP, which allow for rapid clearing and subsequent imaging of three-dimensional sections derived from various tissues using conventional confocal-microscopy. Paper-MAP successfully clear tissues within 1-day, compared to the original-MAP, without significant differences in achieved optical-transparency. As a proof-of-concept, we investigated the vasculature and neuronal-networks of a variety of human and rodent tissues processed via Paper-MAP, in both healthy and diseased contexts, including Alzheimer’s disease and glioma.

Cellulose fibers are a major industrial input, but due to their irregular shape and anisotropic material response, accurate material characterization is difficult. Single fiber tensile testing is the most popular way to estimate the material properties of individual fibers. However, such tests can only be performed along the axis of the fiber and are associated with problems of enforcing restraints. Alternative indirect approaches, such as micro-mechanical modeling, can help but yield results that are not fully decoupled from the model assumptions. Here, we compare these methods with nanoindentation as a method to extract elastic material constants of the individual fibers. We show that both the longitudinal and the transverse elastic modulus can be determined, additionally enabling the measurement of fiber properties in-situ inside a sheet of paper such that the entire industrial process history is captured. The obtained longitudinal modulus is comparable to traditional methods for larger indents but with a strongly increased scatter as the size of the indentation is decreased further.

Microalgal-bacterial consortium is an effective way to meet increasingly stringent standards in wastewater treatment. However, the mechanism of wastewater removal effect has not been properly explained in community structure by phycosphere. And little is known about that the concept of macroecology was introduced into phycosphere to explain the phenomenon. In the study, the algal–bacterial consortia with different ratios of algae and sludge were cultured in same aerobic wastewater within 48 h in photobioreactors (PSBRs). Community structure at start and end was texted by metagenomic analysis. Bray–Curtis similarities analysis based on microbial community showed that there was obvious convergent succession in all consortia, which is well known as “convergence” in macroecology. The result showed that Bray–Curtis similarities at End (overall above 0.88) were higher than these at Start (almost less than 0.66). In terms of community structure, the consortium with 5:1 ratio at Start are the more similar with the consortia at End by which the maximum removal of total dissolved nitrogen (TDN, 73.69%), total dissolved phosphorus (TDP, 94.40%) and NH3-N (93.26%) in wastewater treatment process and biomass production (98.2%) higher than other consortia, according with climax community in macroecology with the highest resource utilization than other communities. Therefore, the macroecology can be introduced into phycosphere to explain the consortium for advanced wastewater treatment and optimization community structure. And the study revealed a novel insight into treatment effect and community structure of algal–bacterial consortia for advanced wastewater treatment, a new idea for to shortening the culture time of consortium and optimize predicting their ecological community structure and predicting ecological community.

This study investigated the effects of electro-dewatering on subsequent low-temperature drying at various potentials and the characteristics of low-temperature air-drying sludge were explored through experiments and multi-physical modeling. Experimental results showed that the extracellular polymeric substance (EPS) content in the sludge was reduced during electro-dewatering process, even the species of organic matter was changed, as well as the dewatered cake tend to form many seepage channels, crack and a certain number of holes. These changes in the properties and structure were conducive to the subsequent low-temperature drying process. For air-drying process, the mass of the sludge cake variation was simulated and results were consistent with the experimental phenomenon. Firstly, the weight of the sludge cake was decreased approximately linearly with time, then tended to stable and reached the dewatering limitation finally. The applied higher electric field intensity (25 V cm−1) in the front-end electro-dewatering were conducive to promote water vapor diffusion activity in air-drying stage. Energy consumption and yield analysis results indicated that the combined technology has lower energy consumption and higher yield than that of directly low-temperature drying.

An automatic feeder for fish feeding was manufactured and evaluated successively. Feed pellet size, air flow rate and feeder screw speed were the most important factors affecting the performance and efficiency of the automatic feeder. It was tested at 3 sizes of pellets (1, 2 and 3 mm), 3 air flow rates (10, 15 and 20 m3 min−1) and 5 screw speeds (180, 360, 540, 720 and 900 rpm). The automatic feeder productivity, efficiency, specific energy consumption and costs were determined. The obtained results indicated that the automatic feeder productivity increases with increasing feed pellets size, air flow rate and rotational speed of screw treatments under study, the automatic feeder efficiency increased with increasing rotational speed of screw until it reached the highest value at 540 rpm and then remain constant at 720–900 rpm and after that decreased with increasing speed. Meanwhile, the specific energy consumption of automatic feeder decreased with increasing feed pellets size, air flow rate and rotational speed of screw treatments under study. The total cost of using automatic feeder ranged from 0.09 to 0.16 EGP kg−1 ($ = 15.63 EGP) for all treatments under study. This feeder will save time, effort and cost for fish industry.

The reason for such enormous efforts in palm oil mill effluent research would be what has been singled out as one of the major sources of pollution in Malaysia, and perhaps the most costly and complex waste to manage. Palm oil mill final discharge, which is the treated effluent, will usually be discharged to nearby land or river since it has been the least costly way to dispose of. Irrefutably, the quality level of the treated effluent does not always satisfy the surface water quality in conformity to physicochemical characteristics. To work on improving the treated effluent quality, a vertical surface-flow constructed wetland system was designed with Pennisetum purpureum (Napier grass) planted on the wetland floor. The system effectively reduced the level of chemical oxygen demand by 62.2 ± 14.3%, total suspended solid by 88.1 ± 13.3%, ammonia by 62.3 ± 24.8%, colour by 66.6 ± 13.19%, and tannin and lignin by 57.5 ± 22.3%. Heat map depicted bacterial diversity and relative abundance in life stages from the wetland soil, whereby bacterial community associated with the pollutant removal was found to be from the families Anaerolineaceae and Nitrosomonadaceae, and phyla Cyanobacteria and Acidobacteria.

Loss of tactile sensations is a major roadblock preventing upper limb-absent people from multitasking or using the full dexterity of their prosthetic hands. With current myoelectric prosthetic hands, limb-absent people can only control one grasp function at a time even though modern artificial hands are mechanically capable of individual control of all five digits. In this paper, we investigated whether people could precisely control the grip forces applied to two different objects grasped simultaneously with a dexterous artificial hand. Toward that end, we developed a novel multichannel wearable soft robotic armband to convey artificial sensations of touch to the robotic hand users. Multiple channels of haptic feedback enabled subjects to successfully grasp and transport two objects simultaneously with the dexterous artificial hand without breaking or dropping them, even when their vision of both objects was obstructed. Simultaneous transport of the objects provided a significant time savings to perform the deliveries in comparison to a one-at-a-time approach. This paper demonstrated that subjects were able to integrate multiple channels of haptic feedback into their motor control strategies to perform a complex simultaneous object grasp control task with an artificial limb, which could serve as a paradigm shift in the way prosthetic hands are operated.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

The electromagnetic pulse (EMP) is either a natural phenomenon caused by a solar storm or can be an effect of the deliberately use of destructive weapons. It is a threat to critical infrastructure systems, including transportation. The construction of transportation means continues to pursue the rapidly accelerating economy and ecological demands while increasingly becoming more dependent on electricity and electronics each day. The paper presents a method that enables driving a vehicle after an impact of EMP of high energy, where the standard protection systems like insulations or protection shields are not efficient, and the vehicle electrical system is destroyed. The device called the Emergency Fueling Unit (EFU) is described. EFU was installed and tested on a truck equipped with a six-cylinder, 11 L CI engine. The truck acceleration test results presented in the paper confirm that the EFU could be effectively used to drive the truck in case of the destruction of its electrical system. The paper’s topic also provides an opportunity to reflect on how and why modern vehicles' powertrains, especially commercial vehicles, are exposed to the influence of phenomena that do not occur in everyday life but can have a disastrous impact on means of transportation and our safety.

In response to the rapid spread of COVID-19, governments across the globe have implemented local lockdowns that have led to increased unemployment and have disrupted local and international transport routes and supply chains. Whilst such efforts aim to slow or stop the spread of the SARS-CoV-2 virus, they have also resulted in increased food insecurity, whether due to reduced incomes or increased food prices. This is the first paper to track food insecurity and its determinants during the pandemic using multi-country and multi-wave evidence. Using data from 11 countries and up to 6 waves of High-Frequency Phone Survey data (household-level surveys) on COVID-19 and its impacts, we use a fixed-effects linear probability model to investigate the socioeconomic determinants of food insecurity during the pandemic for each country using household-level data over multiple waves. We control for socioeconomic characteristics including gender and education of the household head; income and poverty status of the households during the pandemic; safety nets in the form of cash and food assistance; coping strategies adopted by households; and price effects of major food items. Our findings suggest that cash safety nets appear to have been more effective than food in terms of reducing food insecurity during the pandemic; and that those particularly hard hit are female headed-households (highest in Malawi: 0.541, 95% CI 0.516, 0.569; lowest in Cambodia: 0.023, 95% CI 0.022, 0.024), the less educated (highest in Djibouti: − 0.232, 95% CI − 0.221, − 0.244; lowest in Nigeria: 0.006, 95% CI − 0.005, − 0.007), and poorer households (highest in Mali: 0.382, 95% CI 0.364, 0.402; lowest in Chad: 0.135, 95% CI 0.129, 0.142). In line with the existing literature, our results show that, even controlling for income loss and poverty status, those households who had to borrow rather than rely on savings had a higher probability of suffering from food insecurity. Distinct differences in the efficacy of safety nets across the 11 countries, and the differential impact of the pandemic on different groups within societies, suggest in-depth country-specific studies are needed to understand why some countries have coped better than others. Our paper highlights the importance of improving household resilience to future systemic crises, and using evidence-based best practice in the design of relevant policy instruments.

The superstructure rotation method (SRM) has been widely used in recent years due to its rapid construction, low cost and less impact on existing traffic.This paper focuses on construction method and the key parameters related with large angle synchronous rotation construction of T-shape curved rigid frame bridges, taking two bridges of the Wuyi Expressway over the Chengdu-Kunming Railway as the engineering background.The results show that the construction methods used in this project can accomplish the realization of complexed synchronous rotation execution of T-shape curve rigid frame bridge. The construction methods consist of the installation process of ball joint, the design of traction system, accuracy control method and rotation control strategy.The friction coefficients from practical measurements were compared with the analytical ones from existing formulas, and it shows that the calculation method can give good predictions for the friction coefficients at the SRM of curve rigid frame bridge.Finally, the key technologies and determination of key parameters applicable for large angle synchronous rotation construction of curve T-shape rigid frame bridge are summarized. Furthermore, the research results in this paper can provide technical recommendation for the construction of the similar bridges.

Previous studies have reported a decrease in air pollution levels following the enforcement of lockdown measures during the first wave of the COVID-19 pandemic. However, these investigations were mostly based on simple pre-post comparisons using past years as a reference and did not assess the role of different policy interventions. This study contributes to knowledge by quantifying the association between specific lockdown measures and the decrease in NO2, O3, PM2.5, and PM10 levels across 47 European cities. It also estimated the number of avoided deaths during the period. This paper used new modelled data from the Copernicus Atmosphere Monitoring Service (CAMS) to define business-as-usual and lockdown scenarios of daily air pollution trends. This study applies a spatio-temporal Bayesian non-linear mixed effect model to quantify the changes in pollutant concentrations associated with the stringency indices of individual policy measures. The results indicated non-linear associations with a stronger decrease in NO2 compared to PM2.5 and PM10 concentrations at very strict policy levels. Differences across interventions were also identified, specifically the strong effects of actions linked to school/workplace closure, limitations on gatherings, and stay-at-home requirements. Finally, the observed decrease in pollution potentially resulted in hundreds of avoided deaths across Europe. This research had free and open access to all data sources. The work described in this paper has received funding from European Centre for Medium-Range Weather Forecasts (ECMWF) on behalf the European Union through commercial contract Ref. CAMS_95p. Several CAMS Regional Models of the CAMS_50 Service contributed to the present work (CHIMERE, LOTOS-EUROS, MINNI, MOCAGE, MONARCH, SILAM) under CAMS_71 coordination. CAMS_COP066 service provided the lockdown emissions information. O.J. and M.G. thankfully acknowledge the computer resources at Marenostrum and the technical support provided by Barcelona Supercomputing Center (RES-AECT-2020-1-0007). SILAM model runs was also funded by Finnish Academy GLORIA project (No310372). The study was supported by the European Union’s Horizon 2020 Project Exhaustion (Grant ID: 820655). Peer Reviewed "Article signat per 18 autors/es: Rochelle Schneider, Pierre Masselot, Ana M. Vicedo-Cabrera, Francesco Sera, Marta Blangiardo, Chiara Forlani, John Douros, Oriol Jorba, Mario Adani, Rostislav Kouznetsov, Florian Couvidat, Joaquim Arteta, Blandine Raux, Marc Guevara, Augustin Colette, Jérôme Barré, Vincent-Henri Peuch & Antonio Gasparrini "

This paper proposes a deep learning-based patch label denoising method (LossDiff) for improving the classification of whole-slide images of cancer using a convolutional neural network (CNN). Automated whole-slide image classification is often challenging, requiring a large amount of labeled data. Pathologists annotate the region of interest by marking malignant areas, which pose a high risk of introducing patch-based label noise by involving benign regions that are typically small in size within the malignant annotations, resulting in low classification accuracy with many Type-II errors. To overcome this critical problem, this paper presents a simple yet effective method for noisy patch classification. The proposed method, validated using stomach cancer images, provides a significant improvement compared to other existing methods in patch-based cancer classification, with accuracies of 98.81%, 97.30% and 89.47% for binary, ternary, and quaternary classes, respectively. Moreover, we conduct several experiments at different noise levels using a publicly available dataset to further demonstrate the robustness of the proposed method. Given the high cost of producing explicit annotations for whole-slide images and the unavoidable error-prone nature of the human annotation of medical images, the proposed method has practical implications for whole-slide image annotation and automated cancer diagnosis.

Intracellular processes are cascades of biochemical reactions, triggered in response to various types of stimuli. Mathematical models describing their dynamics have become increasingly popular in recent years, as tools supporting experimental work in analysis of pathways and regulatory networks. Not only do they provide insights into general properties of these systems, but also help in specific tasks, such as search for drug molecular targets or treatment protocols. Different tools and methods are used to model complex biological systems. In this work, we focus on ordinary differential equations (ODEs) and Petri nets. We consider specific methods of analysis of such models, i.e., sensitivity analysis (SA) and significance analysis. So far, they have been applied separately, with different goals. In this paper, we show that they can complement each other, combining the sensitivity of ODE models and the significance analysis of Petri nets. The former is used to find parameters, whose change results in the greatest quantitative and qualitative changes in the model response, while the latter is a structural analysis and allows indicating the most important subprocesses in terms of information flow in Petri net. Ultimately, both methods facilitate finding the essential processes in a given signaling pathway or regulatory network and may be used to support medical therapy development. In the paper, the use of dual modeling is illustrated with an example of ATM/p53/NF-$$\kappa$$ κ B pathway. Each method was applied to analyze this system, resulting in finding different subsets of important processes that might be prospective targets for changing this system behavior. While some of the processes were indicated in each of the approaches, others were found by one method only and would be missed if only that method was applied. This leads to the conclusion about the complementarity of the methods under investigation. The dual modeling approach of comprehensive structural and parametric analysis yields results that would not be possible if these two modeling approaches were applied separately. The combined approach, proposed in this paper, facilitates finding not only key processes, with which significant parameters are associated, but also significant modules, corresponding to subsystems of regulatory networks. The results provide broader insight into therapy targets in diseases in which the natural control of intracellular processes is disturbed, leading to the development of more effective therapies in medicine.

Optical chemosensors and ionochromic cellulosic papers based on oxazolidine chromophores were developed for selective photosensing of metal ions and information encryption as security tags, respectively. The oxazolidine molecules have been displayed highly intense fluorescent emission and coloration characteristics that are usable in sensing and anticounterfeiting applications. Obtained results indicated that oxazolidine molecules can be used for selective detection of pb2+ (0.01 M), and photosensing of Fe3+, Co2+ and Ag+ metal ion solutions by colorimetric and fluorometric mechanisms with higher intensity and sensitivity. Also, oxazolidine derivatives were coated on cellulosic papers via layer-by-layer method to prepare ionochromic papers. Prepared ionochromic papers were used for printing and handwriting of optical security tags by using of metal ion solutions as a new class of anticounterfeiting inks with dual-mode fluorometric and colorimetric securities. The ionochromic cellulosic papers can be used for photodetection of metal ions in a fast and facile manner that presence of metal ions is detectable by naked eyes. Also, key-lock anticounterfeiting technology based on ionochromic papers and metal ion solution as ink is the most significant strategy for encryption of information to optical tags with higher security.

This paper studied a tripartite evolutionary game of stakeholders in environmental pollution control. Most previous studies on this issue are limited to a focus on system dynamics with two-party game problems and lack a spatial analysis of strategy evolution. The parameters adopted are too few, and the influencing factors considered are too simple. The purpose of the paper is to introduce more parameters to study, which will have an important impact on the strategy choices of participants and the evolution path of the strategy over time. We construct a tripartite evolutionary game model of sewage enterprises, governments and the public. We establish a payment matrix and replicator equations as our method, and we also implement parameter simulations in MATLAB. In summary, we found that the reward and punishment mechanism plays an important role in environmental pollution control. Specifically: intensifying rewards and penalties will help encourage sewage enterprises to meet the discharge standard and the public to participate in pollution control action. However, increased rewards will reduce government's willingness to adopt incentive strategies; Government's reward for public's participation in the action must be greater than the increased cost of participation; Reducing the cost of sewage enterprise can also encourage them to implement standard emissions. The research presented in this paper further improves standard emissions and designs reasonable reward and punishment mechanism.

Damask rose is a well-established, abundant source of phytochemicals, as well as economically important essential oil—however, its cultivation is demanding and costly. In this paper, extracts from four raw plant materials—Salvia officinalis, Sambucus nigra, Matricaria chamomilla, Calendula officinalis, known to be rich in phenolic compounds, but also far easier to cultivate—were directly compared to those obtained from Rosa × damascena Mill. By combining diverse extraction methodologies (in a Soxhlet apparatus, ultrawave-assisted and microwave-assisted, using supercritical CO2) and complementary in vitro assays (radical scavenging, iron reducing, Folin–Ciocalteau and Al3+ complexation), it was possible to conveniently approximate and compare the phytochemical portfolios of those diverse plants. By factoring in the crop yields of different species, economically important conclusions can be reached—with pot marigold (C. officinalis) seemingly the most viable substitute for damask rose as a source of phenolics. Fatty acid and microelement analyses were also performed, to further enrich the chemical profiles of plant extracts. The paper also aims to collate and redesign multiple colorimetric assays frequently used while studying plant extracts in vitro, but criticized for their lack of correlation to in vivo activity. We show that they remain a viable tool for direct comparison of extraction methodologies, while highlighting their shortcomings.

Emergencies often occur irregularly, such as infectious diseases, earthquakes, wars, floods, the diffusion and leakage of chemically toxic and harmful substances, etc. These emergencies can bring huge disasters to people, even worse, the time left for people to make critical decisions is usually very limited. When an emergency occurs, the most important thing for people is to make reasonable decisions as soon as possible to deal with the current problems, otherwise, the situation may deteriorate further. The paper proposes an emergency decision-making algorithm under the constraints of the limited time and incomplete information, the research is mainly carried out from the following aspects, firstly, we use the data structure of the hesitant fuzzy probabilistic linguistic set to collect the basic data after careful comparison, which has three advantages, (1) considering the hesitation in the decision-making process, each evaluation information is allowed to contain multiple values instead of just one value; (2) each evaluation value is followed by a probability value, which further describes the details of the evaluation information; (3) the data structure allows some probability information to be unknown, which effectively expands the application scope of the algorithm. Secondly, the maximization gap model is proposed to calculate unknown parameters, the model can distinguish alternatives with small differences. Thirdly, all the evaluation information will be aggregated by the dynamic hesitant probability fuzzy weighted arithmetic operator. Subsequently, an instance is given to illustrate the effectiveness and the accuracy of the algorithm proposed in the paper. Finally, the advantages of the proposed algorithm are further demonstrated by comparing it with other outstanding algorithms. The main contribution of the paper is that we propose the maximization gap model to obtain the unknown parameters, which can effectively and accurately distinguish alternatives with small differences.

This paper proposes a visual management scheme of medical things with a color-change radio frequency identification (RFID) tag. The color-change RFID tag employs a specific RFID tag integrated circuit (IC) and a laminated pH-indicating paper. The IC has energy harvesting and switched ground functions, which enable it to generate electricity to the laminated pH-indicating paper. This phenomenon causes electrolysis of NaCl solution absorbed in the laminated pH-indicating paper. Electrolysis generates alkaline matter to change the color of the pH-indicating paper. This paper gives a new and sensitive structure of the laminated pH-indicating paper. The proposed advanced color-change RFID tag with new laminated pH-indicating paper succeeds in changing its color noticeably at a 1 m distance using an RFID reader radiating 1 W radio waves. The color change was observed 3–5 s after starting radio wave irradiation. The results of this experiment also confirm that the changed color can be held for over 24 h. Furthermore, two demonstrations of the visual management system of medical things (patient clothes and sanitizers) are presented.

The uncertainty and fluctuations in graphene characteristic parameters are inevitable issues in both of experimental measurements and numerical investigations. In this paper, the correlations between characteristic parameters (Young’s modulus, Poisson’s ratio and thickness of graphene) and resonant frequencies are analyzed by the Monte Carlo based stochastic finite element model. Based on the Monte Carlo stochastic sampling procedure, the uncertainty in the characteristic parameters are properly propagated and quantified. The displacements and rotation modes of graphene under the resonant vibration computed by the finite element method are verified. Furthermore, the result robustness of stochastic samples is discussed based on the statistic records and probability density distributions. In addition, both the Pearson and Spearman correlation coefficients of the corresponding characteristic parameters are calculated and compared. The work in this paper provides a feasible and highly efficient method for the characteristic parameter correlation discussion by taking uncertainty into consideration.

Fifty years after the experiments of Stanley Milgram, the main objective of the present paper is to offer a paradigm that complies with up-to-date ethical standards and that can be adapted to various scientific disciplines, ranging from sociology and (social) psychology to neuroscience. Inspired by subsequent versions of Milgram-like paradigms and by combining the strengths of each, this paper presents a novel experimental approach to the study of (dis)obedience to authority. Volunteers are recruited in pairs and take turns to be ‘agents’ or ‘victims’, making the procedure fully reciprocal. For each trial, the agents receive an order from the experimenter to send a real, mildly painful electric shock to the ‘victim’, thus placing participants in an ecological set-up and avoiding the use of cover stories. Depending on the experimental condition, ‘agents’ receive, or do not receive, a monetary gain and are given, or are not given, an aim to obey the experimenter’s orders. Disobedience here refers to the number of times ‘agents’ refused to deliver the real shock to the ‘victim’. As the paradigm is designed to fit with brain imaging methods, I hope to bring new insights and perspectives in this area of research.

Space information networks is network systems that can receive, transmit, and process spatial information lively. It uses satellites, stratosphere airships, Unmanned Aerial Vehicles, and other platforms as the carrier. It supports high-dynamic, real-time broadband transmission of earth observations and ultra-long-distance, long-delay reliable transmission of deep space exploration. The deeper the network integration, the higher the system’s security concerns and the more likely SINs will be controlled and destroyed in terms of cybersecurity. How to integrate new IT technologies such as artificial intelligence, digital twins, and blockchain to diverse application scenarios of SINs while maintaining SIN cybersecurity will be a long-term critical technical issue. This study is a review of the security issues for space information networks. First, this paper examines space information networks’ security issues and figures out the relationship between the main security threats, services, and mechanisms. Then, this article selects secure routing and anomaly detection from many security technologies to conduct a detailed overview from two perspectives of traditional methods and artificial intelligence. Subsequently, this paper investigates anomaly detection schemes for spatial information networks and proposes a deep learning-based anomaly detection scheme. Finally, we suggest the potential research directions and opening problems of space information network security. Overall, this paper aims to give readers an overview of the newly emerging technologies in space information networks’ security issues and provide inspiration for future exploration.

Madagascar’s emblematic traveller’s tree is a monospecific genus within Strelitziaceae, the family of the South African bird of paradise. Until now, this endemic genus consisted of a single species: Ravenala madagascariensis Sonn., which is grown everywhere in the tropics as an ornamental plant. The plant is immediately recognizable for its huge fan-forming banana-like leaves and is locally referred to in Magagascar by several vernacular names. “Variants” have been mentioned in the literature, but without any attempt to recognize formal taxa based on diagnostic features. In this paper, we formally describe five new species and fix the application of the name R. madagascariensis to the populations growing on the eastern coast of Madagascar, with the epitype growing in the marshy Fort-Dauphin area in the south. This paper has numerous implications for conservation biology and other domains of life sciences, due to the importance of this genus for the conservation of Madagascan ecosystems, the ornamental plant trade, as well as for its invasive status in several tropical areas.

Every year, around 28,100 journals publish 2.5 million research publications. Search engines, digital libraries, and citation indexes are used extensively to search these publications. When a user submits a query, it generates a large number of documents among which just a few are relevant. Due to inadequate indexing, the resultant documents are largely unstructured. Publicly known systems mostly index the research papers using keywords rather than using subject hierarchy. Numerous methods reported for performing single-label classification (SLC) or multi-label classification (MLC) are based on content and metadata features. Content-based techniques offer higher outcomes due to the extreme richness of features. But the drawback of content-based techniques is the unavailability of full text in most cases. The use of metadata-based parameters, such as title, keywords, and general terms, acts as an alternative to content. However, existing metadata-based techniques indicate low accuracy due to the use of traditional statistical measures to express textual properties in quantitative form, such as BOW, TF, and TFIDF. These measures may not establish the semantic context of the words. The existing MLC techniques require a specified threshold value to map articles into predetermined categories for which domain knowledge is necessary. The objective of this paper is to get over the limitations of SLC and MLC techniques. To capture the semantic and contextual information of words, the suggested approach leverages the Word2Vec paradigm for textual representation. The suggested model determines threshold values using rigorous data analysis, obviating the necessity for domain expertise. Experimentation is carried out on two datasets from the field of computer science (JUCS and ACM). In comparison to current state-of-the-art methodologies, the proposed model performed well. Experiments yielded average accuracy of 0.86 and 0.84 for JUCS and ACM for SLC, and 0.81 and 0.80 for JUCS and ACM for MLC. On both datasets, the proposed SLC model improved the accuracy up to 4%, while the proposed MLC model increased the accuracy up to 3%.

In this research paper, an inverse double V loaded complementary square split ring resonator based double negative (DNG) metamaterial has been developed and examined numerically and experimentally. The electromagnetic (EM) properties of the proposed inverse double V-structure were calculated using computer simulation technology (CST-2019) and the finite integration technique (FIT). The designed metamaterial provides three resonance frequencies are 2.86, 5, and 8.30 GHz, covering S-, C-, and X-bands. The total size of the recommended unit cell is 8 $$\times$$ × 8 $$\times$$ × 1.524 mm3, and a high effective medium ratio (EMR) value of 13.11 was found from it. The − 10 dB bandwidths of this structure are 2.80 to 2.91, 4.76 to 5.17, and 8.05 to 8.42 GHz. The proposed structure's novelty is its small size, simple resonator structure, which provides double negative characteristics, high EMR, maximum coverage band, and required resonance frequencies. Wi-Fi network speeds are generally faster when frequencies in the 5 GHz band are used. Since the proposed structure provides a 5 GHz frequency band, hence the suggested metamaterial can be used in Wi-Fi for high bandwidth and high-speed applications. The marine radars operate in X-band, and weather radar works in S-band. Since the designed cell provides two more resonance frequencies, i.e., 2.86 GHz (S-band) and 8.30 GHz (X-band), the proposed metamaterial could be used in weather radar and marine radar. The design process and various parametric studies have been analyzed in this article. The equivalent circuit is authenticated using the advanced design system (ADS) software compared with CST simulated result. The surface current, E-field, and H-field distributions have also been analyzed. Different types of array structure, i.e., 1 $$\times$$ × 2, 2 $$\times$$ × 2, 3 $$\times$$ × 3, 4 $$\times$$ × 4, and 20 $$\times$$ × 25 is examined and validated by the measured result. The simulated and measured outcome is an excellent agreement for the inverse double V loaded CSSRR unit cell and array. We showed the overall performance of the suggested structure is better than the other structures mentioned in the paper. Since the recommended metamaterial unit cell size is small, provides desired resonance frequency, gives a large frequency band and high EMR value; hence the suggested metamaterial can be highly applicable for Radar and Wi-Fi.

This paper reports on a new configuration for producing highly-aligned electro-spun fibres that can be produced on a static substrate or one where it is hauled off and spooled continuously to enable the production of continuous lengths. The fixture consists of a Vee-shaped polytetrafluorethylene shield at 60° with a 1 cm wide integral rectangular base that is mounted on a copper disk with a 10 cm diameter. Specified concentrations of polyacrylonitrile in dimethyl sulfoxide were electro-spun on to a strip of cellulose paper. In the static setup, approximately 91% of the fibres were deposited to within 3°. When the spooling rig was used, a tape of the cellulose paper was hauled off at 0.07 mm/min, 78% of the fibres were aligned to within 3°. Simulations of the conventional and Vee-shield electro-spinning setups were undertaken and they provided corroboration for the experimental observations with regard to the mechanism responsible for fibre alignment. The feasibility of using this technique to produce 0°/− 45°/+ 45° stacked layers of aligned fibre preform is demonstrated.

Particleboard surface defect detection technology is of great significance to the automation of particleboard detection, but the current detection technology has disadvantages such as low accuracy and poor real-time performance. Therefore, this paper proposes an improved lightweight detection method of You Only Live Once v5 (YOLOv5), namely PB-YOLOv5 (Particle Board-YOLOv5). Firstly, the gamma-ray transform method and the image difference method are combined to deal with the uneven illumination of the acquired images, so that the uneven illumination is well corrected. Secondly, Ghost Bottleneck lightweight deep convolution module is added to Backbone module and Neck module of YOLOv5 detection algorithm to reduce model volume. Thirdly, the SELayer module of attention mechanism is added into Backbone module. Finally, replace Conv in Neck module with depthwise convolution (DWConv) to compress network parameters. The experimental results show that the PB-YOLOv5 model proposed in this paper can accurately identify five types of defects on the particleboard surface: Bigshavings, SandLeakage, GlueSpot, Soft and OliPollution, and meet the real-time requirements. Specifically, recall, F1 score, mAP@.5, mAP@.5:.95 values of pB-Yolov5s model were 91.22%, 94.5%, 92.1%, 92.8% and 67.8%, respectively. The results of Soft defects were 92.8%, 97.9%, 95.3%, 99.0% and 81.7%, respectively. The detection of single image time of the model is only 0.031 s, and the weight size of the model is only 5.4 MB. Compared with the original YOLOv5s, YOLOv4, YOLOv3 and Faster RCNN, the PB-Yolov5s model has the fastest Detection of single image time. The Detection of single image time was accelerated by 34.0%, 55.1%, 64.4% and 87.9%, and the weight size of the model is compressed by 62.5%, 97.7%, 97.8% and 98.9%, respectively. The mAP value increased by 2.3%, 4.69%, 7.98% and 13.05%, respectively. The results show that the PB-YOLOV5 model proposed in this paper can realize the rapid and accurate detection of particleboard surface defects, and fully meet the requirements of lightweight embedded model.

We re-evaluate the findings of one of the most cited and disputed papers in gene-environment interaction (GxE) literature. In 2003, a paper was published in Science in which the authors demonstrated that the relationship between stress and depression is moderated by a polymorphism in the promoter region (5-HTTLPR) of the gene SLC6A4. Replication has been weak and led many to challenge the overall significance of GxE research. Here, we utilize data from Add Health, a large, nationally representative, and well-powered longitudinal study to re-examine the genetic determinants of stress sensitivity. We characterize environmental sensitivity using a genome-wide polygenic indicator rather than relying on one polymorphism in a single candidate gene. Our results provide support for the stress-diathesis perspective and validate the scientific contributions of the original paper.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Effective appointment scheduling (EAS) is essential for the quality and patient satisfaction in hospital management. Healthcare schedulers typically refer patients to a suitable period of service before the admission call closes. The appointment date can no longer be adjusted. This research presents the whale optimization algorithm (WOA) based on the Pareto archive and NSGA-II algorithm to solve the appointment scheduling model by considering the simulation approach. Based on these two algorithms, this paper has addressed the multi-criteria method in appointment scheduling. This paper computes WOA and NSGA with various hypotheses to meet the analysis and different factors related to patients in the hospital. In the last part of the model, this paper has analyzed NSGA and WOA with three cases. Fairness policy first come first serve (FCFS) considers the most priority factor to obtain from figure to strategies optimized solution for best satisfaction results. In the proposed NSGA, the FCFS approach and the WOA approach are contrasted. Numerical results indicate that both the FCFS and WOA approaches outperform the strategy optimized by the proposed algorithm.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

A numerical modeling method is proposed for the melting process of Titanium metals of Titanium alloys powder preparation used for 3D printing. The melting process simulation, which involves the tight coupling between electromagnetic field, thermal field and fluid flow as well as deformation associated during the melting process, is conducted by adopting the finite element method. A two-way coupling strategy is used to include the interactions between these fields by incorporating the material properties dependent on temperature and the coupling terms. In addition, heat radiation and phase change are also considered in this paper. The arbitrary Lagrangian–Eulerian formulation is exploited to model the deformation of Titanium metal during the melting process. The distribution of electromagnetic flux density, eddy current density, temperature, and fluid flow velocity at different time can be determined by utilizing this numerical method. In a word, the method proposed in this paper provides a general way to predict the melting process of electrode induction melting gas atomization (EIGA) dynamically, and it also could be used as a reference for the design and optimization of EIGA.

This paper presents a block-chain enabled inkjet-printed ultrahigh frequency radiofrequency identification (UHF RFID) system for the supply chain management, traceability and authentication of hard to tag bottled consumer products containing fluids such as water, oil, juice, and wine. In this context, we propose a novel low-cost, compact inkjet-printed UHF RFID tag antenna design for liquid bottles, with 2.5 m read range improvement over existing designs along with robust performance on different liquid bottle products. The tag antenna is based on a nested slot-based configuration that achieves good impedance matching around high permittivity surfaces. The tag was designed and optimized using the characteristic mode analysis. Moreover, the proposed RFID tag was commercially tested for tagging and billing of liquid bottle products in a conveyer belt and smart refrigerator for automatic billing applications. With the help of block-chain based product tracking and a mobile application, we demonstrate a real-time, secure and smart supply chain process in which items can be monitored using the proposed RFID technology. We believe the standalone system presented in this paper can be deployed to create smart contracts that benefit both the suppliers and consumers through the development of trust. Furthermore, the proposed system will paves the way towards authentic and contact-less delivery of food, drinks and medicine in recent Corona virus pandemic.

The importance of virus disease outbreaks and its prevention is of growing public concern but our understanding of virus transmission routes is limited by adequate sampling strategies. While conventional swabbing methods provide merely a microbial snapshot, an ideal sampling strategy would allow reliable collection of viral genomic data over longer time periods. This study has evaluated a new, paper-based sticker approach for collection of reliable viral genomic data over longer time periods up to 14 days and after implementation of different hygiene measures. In contrast to swabbing methods, which sample viral load present on a surface at a given time, the paper-based stickers are attached to the surface area of interest and collect viruses that would have otherwise been transferred onto that surface. The major advantage of one-side adhesive stickers is that they are permanently attachable to a variety of surfaces. Initial results demonstrate that stickers permit stable recovery characteristics, even at low virus titers. Stickers also allow reliable virus detection after implementation of routine hygiene measures and over longer periods up to 14 days. Overall, results for this new sticker approach for virus genomic data collection are encouraging, but further studies are required to confirm anticipated benefits over a range of virus types.

Bacnground: Accurate measurement of the femoral neck-shaft angle (NSA) is of great significance for diagnosing hip joint diseases and preoperative planning of total hip arthroplasty. However, the fitting lines of the femoral neck and femoral shaft did not always intersect in 3D space. Thus, it is unclear whether there is a difference between 2D and 3D methods for measuring NSA. Methods: The femoral point cloud datasets from 310 subjects were segmented into three regions, including the femoral head, femoral neck, and femoral shaft using PointNet++. We created a projection plane to simulate the hip anteroposterior radiograph and fitted the femoral neck axis and femoral shaft axis to complete the 2D measurement, while we directly fitted the two axes in space to complete the 3D measurement. Also, we conducted the manual measurement of the NSA. We verified the accuracy of the segmentation and compared the results of the two automatic and manual methods. Results: The Dice coefficient of femoral segmentation reached 0.9746, and MIoU of that was 0.9165. No significant difference was found between any two of the three methods. While comparing the 2D and 3D methods, the average accuracy was 98.00%, and the average error was 2.58°. Conclusion: This paper proposed two accurate and automatic methods to measure the NSA based on a 2D plane and a 3D model respectively. Although the femoral neck and femoral shaft axes did not intersect in 3D space, the NSAs obtained by 2D and 3D methods were basically consistent.

The rapid development of the mobile Internet coupled with the widespread use of intelligent terminals have intensified the digitization of personal information and accelerated the evolution of the era of big data. The sharing and publishing of various big data brings convenience and also increases the risk of personal privacy leakage. In order to reduce users’ privacy leakage that may be caused by data release, many privacy preserving data publishing methods have been proposed by scientists in both academia and industry in the recent years. However, non-numerical sensitive information has natural semantic relevance, and therefore, synonymous linkages may still exist and cause serious privacy disclosures in privacy protection methods based on an anonymous model. To address this issue, this paper proposes a privacy preserving dynamic data publishing method based on microaggregation. A series of indicators are accordingly designed to evaluate the synonymous linkages between the non-numerical sensitive values which in turn facilitate in improving the clustering effect of the microaggregation anonymous method. The dynamic update program is introduced into the proposed microaggregation method to realize the dynamic release and update of data. Experimental analysis suggests that the proposed method provides better privacy protection effect and availability of published data in contrast to the state-of-the-art methods.

Swimming motions of rays that swim using undulation locomotion are not always symmetrical; there may be a phase difference between the left and right pectoral fins. However, few studies on the swimming of rays have mentioned left and right pectoral fin movements. Moreover, the effects of movements of the left and right pectoral fins on swimming have not been clarified. This paper describes a computational study of phase differences of pectoral fin movements in the swimming of rays with the validity of fluid analysis methods. The movement and shape of the ray were made based on previous biological research and pictures. An overset grid was used to reproduce the ray’s complex motions. The analysis was performed under four phase difference conditions: 0 $$T$$ T ($$T$$ T is the period), 0.25 $$T$$ T , 0.5 $$T$$ T , and 0.75 $$T$$ T . The results show that a phase difference between the left and right pectoral fin movements affects swimming stability and maneuverability but not propulsive efficiency. We suggest that the phase difference in pectoral fin movements is essential for the swimming of rays, and rays adjust the phase difference between the movement of the left and right pectoral fins to suit their purpose.

The present paper develops a matrix framework to determine the sustainability of multiple activities simultaneously. We define an activity as an action or process involving multiple resources; each activity depends upon other activities at a higher level. First, the problem of sustainability is framed in the context of an input–output model. Later, an infinite layer approach is adopted to represent different sectors of the economy and both renewable and non-renewable resources. Using the infinite layer approach, the concentration of renewable energy usage is calculated for each activity. The conversion to productive use varies from one resource to another. The current endeavor also focuses on enhancing energy efficiency to reduce non-renewable resource dependency.

Many pore-forming proteins originating from pathogenic bacteria are toxic against agricultural pests. They are the key ingredients in several pesticidal products for agricultural use, including transgenic crops. There is an urgent need to identify novel pore-forming proteins to combat development of resistance in pests to existing products, and to develop products that are effective against a broader range of pests. Existing computational methodologies to search for these proteins rely on sequence homology-based approaches. These approaches are based on similarities between protein sequences, and thus are limited in their usefulness for discovering novel proteins. In this paper, we outline a novel deep learning model trained on pore-forming proteins from the public domain. We compare different ways of encoding protein information during training, and contrast it with traditional approaches. We show that our model is capable of identifying known pore formers with no sequence similarity to the proteins used to train the model, and therefore holds promise for identifying novel pore formers.

Slowing light in a non-dispersive and controllable fashion opens the door to many new phenomena in photonics. As such, many schemes have been put forward to decrease the velocity of light, most of which are limited in bandwidth or incur high losses. In this paper we show that a long metallic helix supports a low-loss, broadband slow wave with a mode index that can be controlled via geometrical design. For one particular geometry, we characterise the dispersion of the mode, finding a relatively constant mode index of $$\sim$$ ∼ 45 between 10 and 30 GHz. We compare our experimental results to both a geometrical model and full numerical simulation to quantify and understand the limitations in bandwidth. We find that the bandwidth of the region of linear dispersion is associated with the degree of hybridisation between the fields of a helical mode that travels around the helical wire and an axial mode that disperses along the light line. Finally, we discuss approaches to broaden the frequency range of near-constant mode index: we find that placing a straight wire along the axis of the helix suppresses the interaction between the axial and high index modes supported by the helix, leading to both an increase in bandwidth and a more linear dispersion.

Rock mass condition assessment during tunnel excavation is a critical step for the intelligent control of tunnel boring machine (TBM). To address this and achieve automatic detection, a visual assessment system is installed to the TBM and a lager in-situ rock mass image dataset is collected from the water conveyance channel project. The rock mass condition assessment task is transformed into a fine-grain classification task. To fulfill the task, a self-convolution based attention fusion network (SAFN) is designed in this paper. The core of our method is the discovery and fusion of the object attention map within a deep neural network. The network consists of two novel modules, the self-convolution based attention extractor (SAE) module and the self-convolution based attention pooling algorithm (SAP) module. The former is designed to detect the intact rock regions generating the attention map, and the latter is designed to improve the performance of classifier by fusing the attention map that focuses on the intact rock regions. The results of SAFN are evaluated from aspects of interpretability, ablation, accuracy and cross-validation, and it outperforms state-of-the-art models in the rock mass assessment dataset. Furthermore, the dynamic filed test show that our assessment system based on the SAFN model is accurate and efficient for automated classification of rock mass.

Al–Mg alloys undergo sensitization when exposed to elevated temperatures, making them susceptible to intergranular corrosion and stress corrosion cracking. Most of the existing research on microstructure effects on sensitization is centered on the effect of intrinsic grain boundary characteristics such as misorientation angle and coincident site lattice (CSL) values. Very few studies have systematically investigated the influence of extrinsic characteristics such as dislocation density. In this paper, the influence of local microstructure characteristics on the sensitization susceptibility of AA5456 was investigated using in situ optical microscopy corrosion experiments and electron back scattering diffraction analysis. The results show a clear trend between the local geometrically necessary dislocation (GND) density and β phase precipitation, with higher GND densities correlating with higher rates sensitized boundaries. This trend held true even for low angle grain boundaries. These results demonstrate the importance of considering factors beyond grain boundary characteristics in determining susceptibility to sensitization.

In this paper we present a novel metamaterial-based antenna simulated using HFSS. The unit cell parameters were extracted using periodic boundary conditions and wave-port excitation. The metamaterial is magnetically coupled to the CPW line, the induced current in the hexagonal ring gives rise to a field perpendicular to the incident one. The antenna can be modeled by an LC circuit. This design achieves a significant impedance bandwidth of 8.47 GHz (S11 = − 10 dB from 72.56 GHz to 81.03 GHz), and a minimum return loss of − 40.79 dB at 76.89 GHz, which clearly indicates good impedance matching to 50Ω. The proposed antenna offers gains from 4.53 to 5.25 dBi, with radiation efficiencies better than 74%. Compactness, simple design layout, a novel design, and good radiation characteristics for this antenna are the main contributions of this work. The antenna can be built on top of a 300 µm thick silicon wafer, for application on HR-SOI-CMOS technology. When compared to other antenna designs for the same frequency band, the proposed antenna achieves very good performance. This design is suitable for the reception stage of long-range automobile radar systems, due to its wide HPBW, as well as E-band applications, such as backhaul systems.

Dental cavity represent one of the widespread illness of the tooth. Method for treating of the tooth is to drill the cavity and to fill the hole with suitable material. Measurements show that during drilling the tooth vibrates with increasing mass that causes unpleasant feeling for patient. The aim of the paper is to give the theoretical explanation for this phenomena and to give suggestion for vibration elimination. During drilling, mass of the tooth is decreasing and the so called ‘reactive force’ occurs. Drilling and reactive force cause tooth vibration. The system is modeled as a nonlinear time variable system. An analytical procedure for solving of the equation of vibration is developed. The solution is assumed in the form of the generalized trigonometric function with time variable amplitude and phase. It is obtained that not only the amplitude but also the frequency of tooth vibration in drilling are increased. In addition to reactive force the drilling velocity, diameter of the drill tool and spindle speed affect the vibration level. The appropriate values of these parameters would eliminate or decrease the patient bad feeling.

In this paper we revisit the concept of mobility entropy. Over time, the structure of spatial interactions among urban centres tends to become more complex and evolves from centralised models to more scattered origin and destination patterns. Entropy measures can be used to explore this complexity, and to quantify the degree of structural diversity of in- and out-flows at different scales and across the system. We use toy models of commuting networks to examine global and local measures, allowing the comparison to occur between different parts of the system. We show that entropy at the link and node level give different insights on the characteristics of the systems, enabling us to identify employment hubs and interdependencies between and within different parts of the system. We compute the measures in the commuting networks of the Northern Powerhouse and Greater South East regions in the UK to examine their relevance when studying real systems of cities. Finally we discuss how these can be used to inform planning and policy decisions oriented towards decentralisation and resilience.

This study briefings the roles of Coriolis, and Lorentz forces on the dynamics of rotating nanofluids flow toward a continuously stretching sheet. The nanoparticles are incorporated because of their unusual qualities like upgrade the thermal transportation, which are very important in heat exchangers, modern nanotechnology, electronics, and material sciences. The primary goal of this study is to improve heat transportation. Appropriate similarity transformations are applied for the principal PDEs to transform into nonlinear dimensionless PDEs. A widely recognized Numerical scheme known as the Finite Element Method is employed to solve the resultant convective boundary layer balances. Higher input in the solvent fraction parameter has a rising effect on the primary velocity and secondary velocity magnitude, and decreasing impact on the distributions of temperature. It is seen that growing contributions of the Coriolis, and Lorentz forces cause to moderate the primary and secondary velocities, but the temperature and concentration functions show opposite trend. The concentration, temperature, and velocities distributions for suction case is prominently than that of injection case, but inverse trend is observed for local Nusselt and Sherwood numbers. These examinations are relevant to the field of plastic films, crystal growing, paper production, heat exchanger, and bio-medicine.