bluuebunny/crossref_metadata_2025 huggingface dataset:
Short-term and long-term survival in critical patients treated by helicopter emergency medical services in Finland: a registry study of 36 715 patients
Authors: Björkman Johannes , Laukkanen-Nevala Päivi , Olkinuora Anna , Pulkkinen Ilkka , Nurmi Jouni
Published: February 2021

Objectives

This study aimed to describe the short-term and long-term mortality of patients treated by prehospital critical care teams in Finland.

Design and setting

We performed a registry-based retrospective study that included all helicopter emergency medical service (HEMS) dispatches in Finland from 1 January 2012 to 8 September 2019. Mortality data were acquired from the national Population Register Centre to calculate the standardised mortality ratio (SMR).

Participants

All patients encountered by Finnish HEMS crews during the study period were included.

Main outcomes

Mortalities presented at 0 to 1 day, 2 to 30 days, 31 days to 1 year and 1 to 3 years for different medical reasons following the prehospital care. Patients were divided into four groups by age and categorised by gender. The SMR at 2 to 30 days, 31 days to 1 year and 1 to 3 years was calculated for the same groups.

Results

Prehospital critical care teams participated in the treatment of 36 715 patients, 34 370 of whom were included in the study. The cumulative all-cause mortality at 30 days was 27.5% and at 3 years was 36.5%. The SMR in different medical categories and periods ranged from 23.2 to 72.2, 18.1 to 22.4, 7.7 to 9.2 and 2.1 to 2.6 in the age groups of 0 to 17 years, 18 to 64 years, 65 to 79 years and ≥80 years, respectively.

Conclusions

We found that the rate of mortality after a HEMS team provides critical care is high and remains significantly elevated compared with the normal population for years after the incident. The mortality is dependent on the medical reason for care and the age of the patient. The long-term overmortality should be considered when evaluating the benefit of prehospital critical care in the different patient groups.
Comparison of outcomes of neurosurgical operations performed before and during the COVID-19 pandemic: a matched cohort study
Authors: Toman Emma , Soon Wai Cheong , Thanabalasundaram Gopiga , Burns Daniel , Petrik Vladimir , Watts Colin , Wykes Victoria , White Anwen
Published: February 2021

Objective

To determine how the first wave of the COVID-19 pandemic affected outcomes for all operatively managed neurosurgical patients, not only those positive for SARS-CoV-2.

Design

Matched cohort (pairwise method).

Setting

A single tertiary neurosurgical referral centre at a large UK Major Trauma Centre.

Participants

During the first COVID-19 wave, 231 neurosurgical cases were performed. These cases were matched to cases from 2019. Cases were matched for age (±10 years), primary pathology and surgical procedure. Cases were excluded from analysis if either the age could not be matched to within 10 years, or the primary pathology or procedure was too unique. After exclusions, 191 cases were included in final analysis.

Outcome measures

Primary outcomes were 30-day mortality and postoperative pulmonary complications. Secondary outcomes included Glasgow Outcome Score (GOS) on discharge, length of stay (LoS), operative and anaesthetic times and grade of primary surgeon. An exploratory outcome was the SARS-CoV-2 status of patients.

Results

There was no significant difference between the pandemic and matched cohorts in 30-day mortality, pulmonary complications, discharge GOS, LoS, operative or anaesthetic times. There was a significant difference in the variation of grade of primary surgeon. Only 2.2% (n=5) of patients had a SARS-CoV-2 positive swab.

Conclusion

During the first UK wave of the COVID-19 pandemic, the mortality, morbidity and functional outcomes of operatively managed neurosurgical patients at University Hospitals Birmingham were not significantly affected compared with normal practice. The grade of primary surgeon was significantly more senior and adds to the growing body of evidence that demonstrates how the pandemic has negatively impacted UK surgical training. Mixing COVID-19 positive, unknown and negative cases did not significantly impact on outcomes and indicates that further research is required to support the implementation of evidence-based surgical pathways, such as COVID-light sites, throughout the next stage of the pandemic.
National Institute for Health and Care Excellence clinical guidelines development principles and processes
Authors: Garbi Madalina
Published: February 2021

Clinical guidelines are developed by professional societies and also, in England, by an independent non-departmental public body, the National Institute for Health and Care Excellence (NICE). Similarities and differences between these guidelines should be viewed in the context of different objectives, responsibilities and roles of guideline developers. This review describes the NICE clinical guidelines development principles and processes with the aim to provide the reader an informed perspective on the recommendations made. NICE clinical guidelines are developed by an appointed independent advisory committee comprising healthcare professionals as well as lay members, supported by a professional team comprising project managers, information specialists, systematic reviewers and health economists. Furthermore, registered stakeholders comprising organisations that have an interest in the guideline topic, or represent people whose practice or care may be directly affected by the guideline, are consulted on the draft scope and draft guidelines. NICE selects a limited number of high impact questions to be answered by the review of evidence, rather than cover a certain topic exhaustively as the clinical guidelines developed by professional societies may do. NICE clinical guidelines recommendations reflect both the clinical effectiveness and the cost-effectiveness of interventions.
Effect of biofuel waste, urea, deer browsing, and vegetation control on Pinus banksiana seedling growth on a dry upland site in central Canada
Authors: Makar Jon , Markham John H.
Published: February 2021

Ash from biofuels and nitrogen fertilizer are increasingly being used as soil amendments. While this can increase tree growth, it can also increase mammalian grazing and competition with vegetation. We applied moderate amounts of ash (1.5 t·ha−1·year−1) and urea (74 kg N·ha−1·year−1) in each of 2 years to a well-drained site in southeastern Manitoba, planted with Pinus banksiana Lamb. Subplots received deer browsing and (or) vegetation control. The ash resulted in an increase in pH in the upper 15 cm of mineral soil from ∼5.7 to 6.6, and the urea created short-term spikes in soil inorganic nitrogen (NH4 and NO3) levels. Urea combined with ash significantly increased seedling relative growth rates in the first 2 years, with seedlings being largest with urea, with or without ash. However, by the fourth year, seedling growth and size did not differ between the amendments. Urea application increased browsing damage to 91%, but only when vegetation was mowed. Browsing guards resulted in seedlings having 1.6 times greater shoot mass by the end of the fourth growing season. These results suggest that on sandy soils in the dry region of central Canada, P. banksiana may get little benefit from ash applications.
Dynamics of local quantum uncertainty among cavity–reservoir qubits
Authors: Ali Mazhar
Published: February 2021

We study dynamics of local quantum uncertainty (LQU) for a system of two cavities and two reservoirs. In the start, the cavities are treated as two qubits which are quantum correlated with each other, whereas reservoirs (also qubits) are neither correlated with each other nor with cavities. We answer two main questions in this work. First, how local quantum uncertainty decays from two quantum correlated cavities and grows among reservoirs. The second question is the examination of LQU developed among four qubits and also shed some light on its dynamics. We observe that LQU develops among reservoirs as kind of mirror image to its decay from cavities. For four qubits, we propose how to compute LQU such that the method is intuitive and analytically computable. We find that among four qubits, LQU starts growing from zero to some maximum value and then decays again to zero as the asymptotic state of cavities is completely transferred to reservoirs. We suggest the experimental setup to implement our results.
Successful application of optical bench in Taiji-1 laser interferometer
Authors: Sha Wei , Fang Chao , Niu Yu ,   On behalf of The Taiji Scientific Collaboration
Published: February 2021

As an important part of laser interferometry system, optical bench is one of the core technologies for the detection of spaceborne gravitational waves. As the first step of the space Taiji program, Taiji-1 provides the measurement accuracy of laser interferometry system better than 100 pm/Hz[Formula: see text](@10 mHz–1 Hz). Taiji-1 is required to be able to track the motion of test mass in inertial sensor. According to the requirements, four interfering optical paths were designed. By adopting an integrated satellite design and selecting the optical and mechanical materials with low linear expansion coefficient, the high stability of optical path was achieved. By using the DOE method, the alignment errors (position/attitude) of four optical paths were all reduced to below 50 [Formula: see text] m/100 [Formula: see text] rad. In the performance test, the accuracy of laser interferometry system was better than 100 pm/Hz[Formula: see text](@10 mHz–1 Hz), and the modulation signal of inertial sensor was successfully detected. The results show that all technical indexes of optical bench have met or exceeded the design requirements.
Automorphism-liftable modules
Authors: Tuganbaev A. A.
Published: February 2021

In this paper, we describe all automorphism-liftable torsion modules over non-primitive hereditary Noetherian prime rings. We also study automorphism-liftable non-torsion modules over not necessarily commutative Dedekind prime rings.
A new theory of fractional differential calculus
Authors: Feng Xiaobing , Sutton Mitchell
Published: February 2021

This paper presents a self-contained new theory of weak fractional differential calculus in one-dimension. The crux of this new theory is the introduction of a weak fractional derivative notion which is a natural generalization of integer order weak derivatives; it also helps to unify multiple existing fractional derivative definitions and characterize what functions are fractionally differentiable. Various calculus rules including a fundamental theorem calculus, product and chain rules, and integration by parts formulas are established for weak fractional derivatives. Additionally, relationships with classical fractional derivatives and detailed characterizations of weakly fractional differentiable functions are also established. Furthermore, the notion of weak fractional derivatives is also systematically extended to general distributions instead of only to some special distributions. This new theory lays down a solid theoretical foundation for systematically and rigorously developing new theories of fractional Sobolev spaces, fractional calculus of variations, and fractional PDEs as well as their numerical solutions in subsequent works.
Multidimensional Benchmarking Framework for AQMs of Network Congestion Control Based on AHP and Group-TOPSIS
Authors: Khatari Maimuna , Zaidan A. A. , Zaidan B. B. , Albahri O. S. , Alsalem M. A. , Albahri A. S.
Published: February 2021

This paper aims to propose a grouping framework for benchmarking the active queue management (AQM) methods of network congestion control based on multicriteria decision-making (MCDM) techniques to assist developers of AQM methods in selecting the best AQM method. Given the current rapid development of the AQM techniques, determining which of these algorithms is better than the other is difficult because each algorithm performs better in a specific metric(s). Current benchmarking studies benchmark the AQM methods from a single incomplete prospective. In each proposed AQM method, the benchmarking was achieved with reference to some evaluation measures that are relatively close to the desired goal being followed during the development of the AQM methods. Furthermore, the benchmarking frameworks of AQM methods are complicated and challenging because of the following reasons: (1) the technical details of the AQM methods are adapted and the input parameters are selected according to the sensitivity of the AQM methods; and (2) a framework is developed and designed for simulating AQM methods, the simulated network and the collected results. For this purpose, a set of criteria for AQM comparison are determined. These criteria are performance, processing overhead and configuration. The benchmarking framework is developed based on the crossover of three groups of multi-evaluation criteria and several AQM methods as a proof of concept. The AQM families that are implemented and utilized in experiments to generate the data that are used as a proof of concept of our proposed framework are the parameter-based (pars) and fuzzy-based AQM methods. Accordingly, constructing the decision matrix (DM) that will be used to generate the final results is necessary. Subsequently, the underlying AQM methods are benchmarked and ranked using MCDM techniques, namely, integrated analytical hierarchy process (AHP) and technique for order of preference by similarity to ideal solution (TOPSIS). The validation was performed objectively. The [Formula: see text] deviation was computed to ensure that the AQM methods ranking undergo systematic ranking. Results illustrate that (1) the integration of AHP and TOPSIS solves the AQM method benchmarking problems; (2) results of the individual TOPSIS context clearly show variances among the ranking results of the six experts; (3) the ranks of the AQM methods obtained from internal and external TOPSIS group decision-making are nearly similar, with random early detection method being ranked as the best one; and (4) in the objective validation, significant differences were found between the groups’ scores, thereby indicating that the ranking results of internal and external TOPSIS group decision-making were valid.
Modeling, simulation and control of a twin-inverted pendulum on a moving cart
Authors: Tamimi Jasem
Published: February 2021

In this paper, a mathematical model of a twin-inverted pendulum on a moving cart has been derived. This is done using the Lagrange–Euler method and, hence, a highly nonlinear mathematical model is resulted from this derivation. These nonlinear and unstable dynamics are written in a simple matrix form. For this challenging system, we use two types of efficient control approaches to treat the control problem of the twin inverted pendulum, namely, linear quadratic regulator (LQR) and nonlinear model predictive control (NMPC). Simulations with several scenarios are also presented to demonstrate the control performances and the model validity.
An Evaluation of Human Conversational Preferences in Social Human-Robot Interaction
Authors: Sirithunge Chapa , Jayasekara A. G. Buddhika P. , Chandima D. P.
Published: February 2021

To generate context-aware behaviors in robots, robots are required to have a careful evaluation of its encounters with humans. Unwrapping emotional hints in observable cues in an encounter will improve a robot’s etiquettes in a social encounter. This article presents an extended human study conducted to examine how several factors in an encounter influence a person’s preferences upon an interaction at a particular moment. We analyzed the nature of conversation preferred by a user considering the type of conversation a robot could have with its user, having the interaction initiated by the robot itself. We took an effort to explore how such preferences differ as the factors present in the surrounding alter. A social robot equipped with the capability to initiate a conversation is deployed to conduct the study by means of a wizard-of-oz (WoZ) experiment. During this study, conversational preferences of users could vary from “no interaction at all” to a “long conversation.” We changed three factors in an encounter which can be different from each other in each circumstance: the audience or outsiders in the environment, user’s task, and the domestic area in which the interaction takes place. Conversational preferences of users within the abovementioned conditions were analyzed in a later stage, and critical observations are highlighted. Finally, implications that could be helpful in shaping future social human-robot encounters were derived from the analysis of the results.
Laboratory Study on Performance Evaluation and Automobile Exhaust Degradation of Nano‐TiO2 Particles‐Modified Asphalt Materials
Authors: Ma Yaozong , Li Lilin , Wang Hua , Wang Wensheng , Zheng Kunkun
Published: February 2021

Automobile exhaust pollution is a serious problem that restricts urban development, and it poses a serious threat to people’s lives and health and even the climate. At present, the treatment of automobile exhaust has attracted people’s attention, and numerous works have been focused on it thereafter. The purpose of the present study is to drive TiO2 nanoparticles application into pavement, and the study present an experimental investigation of performances and automobile exhaust purification of asphalt and its mixture modified by nano‐TiO2. In this work, a series of rheometer properties and pavement performances were studied, including penetration, softening point, ductility, DSR and BBR for asphalt binder, conventional pavement performances, and creep test for asphalt mixture. Moreover, the photocatalytic degradation test of automobile exhaust was conducted to assess degradation of TiO2 nanoparticles in the asphalt mixture on automobile exhaust. Results indicate that the TiO2 nanoparticle was beneficial to increase the viscosity and reduce the temperature sensitivity, which would enhance its high‐temperature stabilization capability of asphalt. Meanwhile, nano‐TiO2 can significantly enhance the rheometer properties of asphalt and its capacity of high‐temperature antirutting, and its low‐temperature performance could also comply with the specification. Besides, the incorporation of nano‐TiO2 in mixtures could effectively enhance the antirutting and anticracking as well as water stabilization. Moreover, the nano‐TiO2‐modified asphalt mixture possesses a positive impact on photocatalytic degradation of CH and NOx, which could provide a reference for the treatment of automobile exhaust. The photocatalytic degradation effect of asphalt mixtures modified by nano‐TiO2 on NOx is significantly better than that of CH.
Can a Manufacturer Get Better off When Providing Product Sharing Services?
Authors: Li Xiaozheng , Hu Xiaojian , Qiu Ju , Zhu Xinxuan
Published: February 2021

The emerging product sharing trend poses challenges for manufacturers. Although the cost of purchasing products is decreased by adopting product sharing, consumers must accept that their demand cannot be responded to instantly and must use unfamiliar shared products. There are unavoidable inconveniences that are inherent in product sharing that directly affect consumers’ choices and further affect manufacturers’ decisions about providing sharing services. However, few papers have focused on the impact of such factors. In this paper, we aim to study how the unavoidable inconvenience costs and operational costs affect the manufacturer’s decision on whether to provide sharing services. First, low inconvenience cost and operational cost encourage the manufacturer to provide sharing services. High product quality weakens the influence of these two factors, while strengthening the influence of the pooling effect on the manufacturer’s provision decision. Second, the sharing market cannibalizes the sales demand when inconvenience cost is low and product quality is high. Third, the provision of sharing services is a win-win situation for consumers and the manufacturers of low-quality products.
Application of Computer Technology in Optimal Design of Overall Structure of Special Machinery
Authors: Guo Caiping
Published: February 2021

With the transformation and upgrading of my country’s industrial structure, the level of manufacturing automation has gradually improved. According to research, the design of mechanical products is mostly completed by improvement or innovation on the basis of existing design knowledge. Knowledge reuse is a technique to ensure the maximization of design resource utilization by reusing design knowledge. This article applies knowledge reuse technology to the development and design of mechanical products. By integrating the technical logic of the functional analysis system with the development of quality functions, the transformation of customer demand information and product function design is realized, and the task of the product design plan analysis phase is completed. This paper uses the finite element analysis software ANSYS to explore a new nonlinear finite element modeling method and conducts simulation experiments. At the same time, this paper improves the genetic algorithm, which effectively improves the optimization efficiency and completes the parameter optimization under multiobjective and multistructure conditions. From the experimental results, it takes 328.64 seconds for the basic genetic algorithm to search for the optimal solution of the complex problem. The improved time is shortened to 86.31 seconds, and the efficiency is increased by 73.74%. This shows that the improved genetic algorithm has better robustness and can find the optimal solution in a shorter calculation time. For complex problems such as the optimization of the overall structure of special machinery, the improved genetic algorithm obviously helps to improve the optimization efficiency and improves the effectiveness and pertinence of product design schemes.
A Variational Principle for the Steady-State Heat Transfer Process in a Rigid Continuous Mixture
Authors: Saldanha da Gama Rogério M.
Published: February 2021

The subject of this paper is the steady-state heat transfer process in a rigid mixture with

N

continuous constituents, each of them representing a given continuous body. A continuous mixture consists of a convenient representation for bodies composed by several different materials or phases, in which the actual interfaces do not allow an adequate Classical Continuum Mechanics approach, once that the boundary conditions make the mathematical description of the problem unfeasible (as for instance in reinforced concrete, polymer strengthened concrete, and porous media). The phenomenon is mathematically described by a set of

N

partial differential equations coupled by temperature-dependent terms that play the role of internal energy sources. These internal energy sources arise because, at each spatial point, there are different temperatures, each one associated with one constituent of the mixture. The coupling among the partial differential equations arises from the thermal interchange among continua in a thermal nonequilibrium context (different temperature levels). In this work, it is presented a functional whose minimization is equivalent to the solution of the original steady-state problem (variational principle). The features of this functional give rise to proofs of solution existence and solution uniqueness. It is remarkable that, with the functional to be proposed here, instead of solving a system of

N

coupled partial differential equations, we need to look only for the minimum of a single functional.
Celecoxib-Loaded Electrospun Fibrous Antiadhesion Membranes Reduce COX-2/PGE2 Induced Inflammation and Epidural Fibrosis in a Rat Failed Back Surgery Syndrome Model
Authors: Wang Wei , Wang Yunhao , Lou Tengfei , Ding Mingqian , Li Juehong , Xiong Hao , Yao Zhixiao , Ma Yingying , Chen Huajiang , Liu Shenghe
Published: February 2021

To date, failed back surgery syndrome (FBSS) remains a therapy-refractory clinical condition after spinal surgery. The antiadhesion membrane is applied to prevent FBSS by isolating fibrosis; however, the inflammation stimulated by the foreign body and surgical trauma needs to be further resolved simultaneously. Therefore, we developed new electrospun polycaprolactone (PCL) fibrous membranes loaded with celecoxib (CEL) to prevent fibrosis and inflammation associated with FBSS. The CEL-loaded PCL fibers were randomly distributed, and the drug was released over two weeks. Fluorescence micrographs revealed that the fibroblasts proliferated less on the PCL-CEL fibrous membranes than in the PCL group and the blank control. In the rat laminectomy model after 4 weeks, magnetic resonance imaging of epidural fibrosis was least in the PCL-CEL group. Expression of COX-2 and PGE2 was lower in the PCL-CEL group. It concluded that the CEL-loaded PCL membrane could reduce fibrosis and inflammation in a rat model of FBSS via COX-2/PGE2 signaling pathways.
Research on Sensitive Measuring Points for Vibration Fault of NC Turret Based on Energy Flow and Transfer Path
Authors: Chen Fei , Zhang DeCong , Luo Wei , Xu Binbin
Published: February 2021

Some equipment fault measurement points are difficult to determine. Thus, this study proposes a method using energy flow and transfer path to select sensitive measurement points. Firstly, based on the energy flow theory of the shell, the energy flow is taken as the physical quantity to describe the energy transfer of the structure vibration, and the energy-based transfer path analysis method is established. Secondly, the simulation model of the finite element energy flow was established by focusing on the NC turret, and the vector image of the energy flow transfer path of the NC turret shell was created. For the relationship between the vector images of the experimental and simulation energy flows, the validity of the finite element energy flow simulation results is verified. Lastly, three abnormal areas of the NC turret shell are identified by comparing and analyzing the energy flow vector images of the NC turret in the healthy and fault states, taking the poor meshing fault of the grooves as an example. By choosing nine test points in the abnormal areas and calculating the distribution rate of the transfer paths between the test points to the joint surfaces of the fluted disc, the energy flow distribution rate of the different fault positions to the test points is obtained. Calculation results enabled us to identify three measuring points that can accurately distinguish the fault location for a typical fault mode. This research combined energy flow theory and transfer path analysis method to determine the vibration fault sensitive measuring points of NC equipment. The proposed method is practical in the field of fault diagnosis and has broad application prospects.
Impact of distributed generation on the Nigerian power network
Authors: Fasina Taiwo , Adebanji Bankole , Abe Adewale , Ismail Isiaka
Published: February 2021

Distributed generations (DG) are being installed at increasing rates, both in developed and developing countries. The increasing number of DG connected to the distribution system could have a significant impact on the power system operation. This paper presents a case study investigating the impact of grid-connected DG on the Nigerian power network in terms of bus voltages and network losses. The results showed that without DG, some of the bus voltage magnitudes of the test system were outside the permissible voltage limit of 0.95pu≤Vi≤1.05p.u. However, with DG connected, the voltage magnitudes were improved to allowable values. The network active power loss was reduced by 12.03% from 85.60MW to 75.30MW. In this way, the power system becomes more efficient and secured.
Optimal placement of facts devices to reduce power system losses using evolutionary algorithm
Authors: Khalid Zarkani Mahmood , Sahib Tukkee Ahmed , Jasim Alali Mohammed
Published: February 2021

The rapid and enormous growths of the power electronics industries have made the flexible AC transmission system (FACTS) devices efficient and viable for utility application to increase power system operation controllability as well as flexibility. This research work presents the application of an evolutionary algorithm namely differential evolution (DE) approach to optimize the location and size of three main types of FACTS devices in order to minimize the power system losses as well as improving the network voltage profile. The utilized system has been reactively loaded beginning from the base to 150% and the system performance is analyzed with and without FACTS devices in order to confirm its importance within the power system. Thyristor controlled series capacitor (TCSC), unified power flow controller (UPFC) and static var compensator (SVC) are used in this research work to monitor the active and reactive power of the carried out system. The adopted algorithm has been examined on IEEE 30-bus test system. The obtained research findings are given with appropriate discussion and considered as quite encouraging that will be valuable in electrical grid restructuring.
Wireless electric energy transmission system and its recording system using PZEM004T and NRF24L01 module
Authors: Dwiyanto Tobi Markus , Van Harling Vina N.
Published: February 2021

Electrical energy can not be separated from the name kWh Meter, a tool used to measure and record the amount of electrical energy usage has a shortage of kWh meters can not be monitored remotely how much energy is used, so it is rather inconvenient for PLN officials to check the use of electricity for postpaid customers. This research was conducted to design a prototype of a wireless electrical energy transmission system and design a wireless electrical energy recording system using the NRF24L01 wireless transmitter module and the PZEM004T kWh meter module. The design in this study uses the principle of electromagnetic induction to transfer electrical energy at close range, while to transmit data, the authors use the NRF24L01 module. Besides, the authors use the PZEM004T module to measure various magnitudes. Based on the results of observations and measurements of the design of the tool, the authors found that the transmission of electrical energy using electromagnetic induction is not effective for longer distances because the energy lost in the air is getting bigger. So this technology needs to be further investigated. Besides, the measurement of electrical quantities using the PZEM module has a small difference (under 2%) with measurements using a multimeter, so it can be said that the measurement with the PZEM004T module is effective. 
Fusion for medical image based on discrete wavelet transform coefficient
Authors: Yaseen Hasan Zahraa , Altaie Rusul , Al-kadum Hassan Hawraa Abd
Published: February 2021

More recent digital camera introduced enormous facilities for users from different specifications to take images easily, but the user still wants to improve these images, which it contains different problems like ambiguous and colors is not clear, because not enough light, cloudy weather, bright light, dark region and it's taken from remote distances. This paper aims to use a new approach for fusion images by using a wavelet coefficient based on PSNR and SNR measure (the technical result) instead of using the max, min, average values, and so on in the previous methods. The wavelet coefficient of each sub band is compared between them, the sub band had a value higher of measure is selected for fusion. Firstly, a discrete wavelet transform has been applied to the medical images with 2level. Then, the peak signal to noise ratio and signal to noise ratio measures have been computed for each sub-band. After that PSNR and SNR values have been compared for each sub-band to opposite sub-band and it selected the better value of measures. Secondly, PSNR and SNR values have been gathered for each image. Then select the image that contains value higher PSNR and lower value of SNR for purpose fusion. Finally, perform an inverse discrete wavelet on the fused image to transform it from the frequency to the spatial domain. The results of the work showed that the wavelet coefficient is used to preserve the image details and removed the noise. PSNR value of 1level of dwt is higher than 2level. This paper makes the image more clearer and informative than the original images. 
Accident vehicle types classification: a comparative study between different deep learning models
Authors: Anwer Mardin A. , Shareef Shareef M. , Ali Abbas M.
Published: February 2021

Classifying and finding type of individual vehicles within an accident image are considered difficult problems. This research concentrates on accurately classifying and recognizing vehicle accidents in question. The aim to provide a comparative analysis of vehicle accidents. A number of network topologies are tested to arrive at convincing results and a variety of matrices are used in the evaluation process to identify the best networks. The best two networks are used with faster recurrent convolution neural network (Faster RCNN) and you only look once (YOLO) to determine which network will identifiably detect the location and type of the vehicle. In addition, two datasets are used in this research. In consequence, experiment results show that MobileNetV2 and ResNet50 have accomplished higher accuracy compared to the rest of the models, with 89.11% and 88.45% for the GAI dataset as well as 88.72% and 89.69% for KAI dataset, respectively. The findings reveal that the ResNet50 base network for YOLO achieved higher accuracy than MobileNetV2 for YOLO, ResNet50 for Faster RCNN with 83%, 81%, and 79% for GAI dataset and 79%, 78% and 74% for KAI dataset.
Secure image hiding in speech signal by steganography-mining and encryption
Authors: Khaleel Amal Hameed , Abduljaleel Iman Qays
Published: February 2021

Information hiding techniques are constantly evolving due to the increased need for security and confidentiality. This paper proposes a working mechanism in three phases. The first phase includes scrambling the values of the gray image depending on a series of keys that are generated using a quantum chaotic map. The second phase generates hybrid keys by mixing a Zaslavsky and a 3D Hanon map that are used to encrypt the gray image values produced after the scramble. Finally, in the third phase, a new algorithm is suggested to hide the encrypted gray image at random locations within a speech file.  This algorithm includes the LSB algorithm to determine the hidden bits and the zero-crossing K-means algorithm in selecting locations mining in a scattered manner so that hackers cannot easily retrieve the hidden data of any hacked person. Also used a fractional fourier transform to choose magnitude value as specific data to hide encoded image data. The measures MSE, PSNR, NSCR, and UACI are using to measure the work efficiency in the encryption algorithm, and in measuring the efficiency of the hidden algorithm, use the measures SNR, PSNR, and MSE. The results of the paper are encouraging and efficient compared to other algorithms that performed the same work. Hence our results show the larger the image dimensions used, the better the values.
Binding site identification of COVID-19 main protease 3D structure by homology modeling
Authors: Adebiyi Marion , O. Olugbara Oludayo
Published: February 2021

The influx of coronavirus in 2019 (COVID-19) from Wuhan of China has led to a global pandemic, undesirable hiatus, and recorded millions of infection cases with several deaths worldwide. The strain of COVID-19 has neither known treatments nor vaccines, but recent studies have shown that a few of its enzymes may have been considered as potential drug target. Since its influx, the virus has been well-studied, but a lot is not known about its protease yet.  The purpose of this work was to identify the binding site in-silico and present 3D structure of COVID-19 main protease (Mpro) by homology modeling through multiple alignment followed by optimization and validation. The modeling was done by Swiss-Model template library and basic local alignment search tool (BLAST). The obtained homotrimer oligo-state model was verified for reliability using structural validation software such as PROCHECK, Verify3D, MolProbity and QMEAN. The HHBlits software was used to determine the structures that matched the target sequence by evolution. Best template, 6u7h.1.A was used to build a tertiary structure for Mpro with ProMod3 3.0.0 on the Swiss-Model workspace. Self-optimized prediction method with alignment (SOPMA) was applied to compute features of the secondary structure. The verification of quality of COVID-19 structure through Ramachandran plot showed an abundance of 99.3% of amino acid residues in allowed regions while 0.1% in disallowed region. The Verify3D rated the structure a 90.87% PASS of residues having an average 3D-1D score of at least 0.2, which validates a good environment profile for the COVID-19 Mpro model. The features of the secondary structure indicated that the modeled 3D structure of Mpro contains 32.05% α-helix and 37.17% random coil with 25.92 extended strand. DeepSite algorithm elucidates the binding site area that captured local patterns in the structure and exposed the surface cavity of the binding pocket of this protein. The main result of this study suggests that blocking expression of the protein may constitute an efficient approach for transmission blockage. Hence, our thought is that Mpro of COVID-19 may be considered a potential drug target. Nevertheless, more experimental analyses, verification and validation experiments will be required as a targeted drug or vaccine design against COVID-19 virus.
Key exchange based on Diffie-Hellman protocol and image registration
Authors: Rimani Rachid , Hadj Said Naima , Ali Pacha Adda , Ozer Ozen
Published: February 2021

Nowadays, with the advences in ICT and rapid development of mobile internet; media information shared on the various communication networks requires the existence of adequate security measures. Cryptography becoming an effective way to meet these requirements and for maintain the confidentiality. However, communicating with encrypted messages requires secret key exchange, which is a part of a complex protocol. In this paper, we propose a new method for exchanging key based on Diffie-Hellman protocol and image registration with fast fourier transform, the principle of this method consists to concealing the key in a set of transformed images. Therefore, image registration allows finding transformations between images, which become a tool for recovering the key by the receiver.
Extracting numerical data from unstructured Arabic texts (ENAT)
Authors: K. AL-Mashhadany Abeer , N. Hamood Dalal , Sadiq Al-Obaidi Ahmed T. , K. Al-Mashhsdany Waleed
Published: February 2021

Unstructured data becomes challenges because in recent years have observed the ability to gather a massive amount of data from annotated documents. This paper interested with Arabic unstructured text analysis. Manipulating unstructured text and converting it into a form understandable by computer is a high-level aim. An important step to achieve this aim is to understand numerical phrases. This paper aims to extract numerical data from Arabic unstructured text in general. This work attempts to recognize numerical characters phrases, analyze them and then convert them into integer values. The inference engine is based on the Arabic linguistic and morphological rules. The applied method encompasses rules of numerical nouns with Arabic morphological rules, in order to achieve high accurate extraction method. Arithmetic operations are applied to convert the numerical phrase into integer value. The proper operation is determined depending on linguistic and morphological rules. It will be shown that applying Arabic linguistic rules together with arithmetic operations succeeded in extracting numerical data from Arabic unstructured text with high accuracy reaches to 100%.
New text steganography method using the arabic letters dots
Authors: R. Khekan Ahlam , Wajeh Majeed Hiba Mohammed , Ahmed Adeeb Omer F.
Published: February 2021

With the increasing technological and electronic development, methods have been developed to hide important information using text steganography as a new technology, since it is not noticeable and easy to send and receive. The use of the Arabic language is one of the new methods used to hide data. In this work, we preview our method that depends to use the part of Arabic language properties to embed the secret English message in to cover text to create text steganography. More than half of the Arabic characters contain dots. Several characters have upper dots and others have lower dots. Some have one dot others have two dots. Few have even three dots. In this new idea, we will use the dots of charters to embed the English secret message. First, we will compress the secret message by using the 5-Bit Encoding (T-5BE) to make the cover text able to embed more bits of the secret message by 37.5%. Then we start using the Arabic semantic dictionary to correct the hiding path and enhancement the stego-cover text to eliminate errors caused by switching words. In this research, we were able to extract experimental results that show that the proposed model achieves high masking accuracy in addition to the storage capacity of the cover text.
Fast learning neural network based on texture for Arabic calligraphy identification
Authors: Kawther Hussein Ahmed
Published: February 2021

Arabic calligraphy is considered a sort of Arabic writing art where letters in Arabic can be written in various curvy or segments styles. The efforts of automating the identification of Arabic calligraphy by using artificial intelligence were less comparing with other languages. Hence, this article proposes using four types of features and a single hidden layer neural network for training on Arabic calligraphy and predicting the type of calligraphy that is used. For neural networks, we compared the case of non-connected input and output layers in extreme learning machine ELM and the case of connected input-output layers in FLN. The prediction accuracy of fast learning machine FLN was superior comparing ELM that showed a variation in the obtained accuracy. 
Towards design strong emergency and COVID-19 authentication scheme in VANET
Authors: Leaby Akeel Kassim , Yassin A. , Hasson Mushtaq , Rashid Abdullah
Published: February 2021

The wide use of vehicular ad hoc networks (VANETs) in the last decade hasled many researchers to find  efficient and reliable methods to obtain the desired benefits and offer services, such as healthcare and traffic management. However, VANETs suffer from security issues represented by authentication and data integrity. In thispaper, we propose a robust  mutual authentication scheme based on elliptic curve cryptography (ECC), cryptography hash function, and a pseudonym. The  proposed work was twofold in focus: first, on healthcare in emergency cars which use VANETs, and second, on overcoming security issues, such as resisting familiar attacks (e.g. insider attacks and reply attacks). Because of the serious situation generated by the worldwide outbreak of the Covid-19 epidemic, we also found this research valuable in supporting global efforts to combat the rapid spread of this virus, by finding the safest and fastest routes to epidemic treatment centres for medical staff, assistance teams in medical  operations, fumigation control, and all work teams associated with disease control. This research attempts to contribute by proposing a special signal  used to define epidemic teams. The best route, fast route can be chosen by using VANETs infrastructure. This scheme also deals with metric security features, such as key management, data integrity, and data privacy. In the communication and computation  cost, we  noticed  that our proposed scheme  achieved  good results compared with the related works.
Iluminou-se a fonte da fala
Authors: Carvalho Márcio de , Leal Izabela Guimarães Guerra
Published: February 2021

O artigo oferece uma leitura inicial da tradução poética de Josely Vianna Baptista para os cantos sagrados dos mbyá-guarani do Cuairá, os quais apresentam a cosmologia guarani, assim como a tradução feita por Haroldo de Campos da cena da origem segundo a memória hebraica. De forma breve, apontará aproximações fortuitas e eventuais distanciamentos entre as mitopoéticas e identificará o projeto de tradução proposto por esses dois poetas tradutores. Sobretudo, demonstrará o diálogo entre as duas produções através da palavra fundante que, em sua vigência dialética, cria mundos e estabelece a terra, o humos, o homem. Propõe uma reflexão acerca do papel da linguagem e da oralidade para os mbyá e para os hebreus, a fim de escutar o construto de sua natureza. Este artigo aponta como o leitor tem acesso a eventos de cultura através das transculturações realizadas por esses poetas.
Gerações em conflito nas narrativas de Etgar Kéret
Authors: Steinberg Gabriel
Published: February 2021

A sexta antologia de narrativas curtas Takalá Biktzê hagalaksia (Um incidente nos confins da Galáxia), rendeu ao escritor israelense Etgar Kéret o prêmio Sapir em 2018. Como é marca de sua escrita, suas narrativas se dirigem ao leitor numa linguagem coloquial e informal. Sua escrita por vezes bem humorada tem como personagens pessoas comuns, que em situações peculiares tem um comportamento extremo e até bizarro.
Toward a Kernel-Based Uncertainty Decomposition Framework for Data and Models
Authors: Singh Rishabh , Principe Jose C.
Published: February 2021

This letter introduces a new framework for quantifying predictive uncertainty for both data and models that relies on projecting the data into a gaussian reproducing kernel Hilbert space (RKHS) and transforming the data probability density function (PDF) in a way that quantifies the flow of its gradient as a topological potential field (quantified at all points in the sample space). This enables the decomposition of the PDF gradient flow by formulating it as a moment decomposition problem using operators from quantum physics, specifically Schrödinger's formulation. We experimentally show that the higher-order moments systematically cluster the different tail regions of the PDF, thereby providing unprecedented discriminative resolution of data regions having high epistemic uncertainty. In essence, this approach decomposes local realizations of the data PDF in terms of uncertainty moments. We apply this framework as a surrogate tool for predictive uncertainty quantification of point-prediction neural network models, overcoming various limitations of conventional Bayesian-based uncertainty quantification methods. Experimental comparisons with some established methods illustrate performance advantages that our framework exhibits.
Do long-tailed macaques avoid large heterospecific carcasses?
Authors: Peterson Jeffrey V. , Fuentes Agustín
Published: February 2021

This anecdotal observation details the response of long-tailed macaques (Macaca fascicularis) to a heterospecific carcass. The subgroup of macaques we were following abruptly changed their direction of travel upon reaching a tree line while displaying silent vigilance behaviour. We later discovered a dog carcass in the area and concluded their behaviour may have been in response to the smell of that carcass. The carcass was not visible from the response point at the tree line due to its distance from that point (approximately 30 meters) and the uneven and densely vegetated terrain between. The macaques were therefore most likely responding to scent cues from the carcass. We suggest the observed vigilance behaviour is excessive under a strictly pathogen-avoidance explanation and may be understood as a response to a cue of potential predation risk. We review alternative explanations and suggest future research on nonhuman primate heterospecific carcass avoidance is necessary to fully assess the potential relation to perceived risk of predation.