bluuebunny/crossref_metadata_2025 huggingface dataset:
Patient Safety during ECMO Transportation: Single Center Experience and Literature Review
Authors: Puslecki Mateusz , Baumgart Konrad , Ligowski Marcin , Dabrowski Marek , Stefaniak Sebastian , Ladzinska Malgorzata , Goszczynska Ewa , Marcinkowski Pawel , Olasinska-Wisniewska Anna , Klosiewicz Tomasz , Pawlak Aleksander , Zielinski Marcin , Puslecki Lukasz , Podlewski Roland , Szarpak Lukasz , Jemielity Marek , Perek Bartlomiej
Published: February 2021

Background. Extracorporeal membrane oxygenation (ECMO) has been proven to support in lifesaving rescue therapy. The best outcomes can be achieved in high-volume ECMO centers with dedicated emergency transport teams. Aim. The aim of this study was to analyze the safety of ECMO support during medical transfer on the basis of our experience developed on innovation cooperation and review of literature. Methods. A retrospective analysis of our experience of all ECMO-supported patients transferred from regional hospital of the referential ECMO center between 2015 and 2020 was carried out. Special attention was paid to transportation-related mortality and morbidity. Moreover, a systematic review of the Medline, Embase, Cochrane, and Google Scholar databases was performed. It included the original papers published before the end of 2019. Results. Twelve (5 women and 7 men) critically ill ECMO-supported patients with the median age of 33 years (2–63 years) were transferred to our ECMO center. In 92% (n = 11) of the cases venovenous and in 1 case, venoarterial supports were applied. The median transfer length was 45 km (5–200). There was no mortality during transfer and no serious adverse events occurred. Of note, the first ECMO-supported transfer had been proceeded by high-fidelity simulations. For our systematic review, 68 articles were found and 22 of them satisfied the search criteria. A total number of 2647 transfers were reported, mainly primary (90%) and as ground transportations (91.6%). A rate of adverse events ranged from 1% through 20% but notably only major complications were mentioned. The 4 deaths occurred during transport (mortality 0.15%). Conclusions. Our experiences and literature review showed that transportation for ECMO patients done by experienced staff was associated with low mortality rate but life-threatening adverse events might occur. Translational simulation is an excellent probing technique to improve transportation safety.
Efficient Anonymous Data Authentication for Vehicular Ad Hoc Networks
Authors: Yu Ping , Ni Wei , Yu Guangsheng , Zhang Hua , Liu Ren Ping , Wen Qiaoyan
Published: February 2021

Vehicular ad hoc network (VANET) encounters a critical challenge of efficiently and securely authenticating massive on-road data while preserving the anonymity and traceability of vehicles. This paper designs a new anonymous authentication approach by using an attribute-based signature. Each vehicle is defined by using a set of attributes, and each message is signed with multiple attributes, enabling the anonymity of vehicles. First, a batch verification algorithm is developed to accelerate the verification processes of a massive volume of messages in large-scale VANETs. Second, replicate messages captured by different vehicles and signed under different sets of attributes can be dereplicated with the traceability of all the signers preserved. Third, the malicious vehicles forging data can be traced from their signatures and revoked from attribute groups. The security aspects of the proposed approach are also analyzed by proving the anonymity of vehicles and the unforgeability of signatures. The efficiency of the proposed approach is numerically verified, as compared to the state of the art.
Modelling the Triaxial Compression Behavior of Loess Using the Disturbed State Concept
Authors: Xu Yali , Guo Panpan , Wang Yixian , Zhu Cheng-Wei , Cheng Kang , Lei Gang
Published: February 2021

This paper investigates the triaxial compression behaviour of Q3 loess soil and the construction of a constitutive model accounting for the structural effect of loess on the basis of the disturbed state concept. By analyzing the triaxial compression testing results, we have established a new disturbing function with respect to the volumetric and shear moduli parameters. A research into the evolution laws of the disturbing function was also conducted, followed by the construction of a constitutive model for loess soil as well as the verification of the constitutive model with model test results. The results indicate that the double‐parameter disturbing function evolves in an exponential form, capturing well the effect of moisture content and confining pressure on the loess structural behavior. The parameters of the constructed constitutive model based on the disturbed state are easy to be obtained and have clarified physical meanings. Considering the effectiveness in capturing the structural behavior of the loess, the constructed constitutive model has a great potential to be applied in the engineering practice in the loess area. The constructed constitutive model based on the disturbed state concept provides new ideas for the study of the structural constitutive model of loess, which is theoretically significant.
Hirudo Lyophilized Powder Ameliorates Renal Injury in Diabetic Rats by Suppressing Oxidative Stress and Inflammation
Authors: Yang Fan , Li Yachun , Guo Shuai , Pan Yongmei , Yan Cuihuan , Chen Zhiqiang
Published: February 2021

As diabetic nephropathy (DN) is one of the most common and destructive microvascular complications of diabetes mellitus, the goal of this study, therefore, was to investigate the renal protective effect and latent mechanisms of Hirudo lyophilized powder on diabetic rats. In this study, all rats were randomly assigned into the control group and diabetic group. The rats of diabetic group were injected with low-dose STZ (35 mg/kg) intraperitoneal plus high-fat diet to induce diabetes. Then, the successful diabetic model rats were weighed and randomly assigned into four groups: (1) diabetic model group (DM group); (2) Hirudo lyophilized powder 0.3 g/kg treatment group (SL group); (3) Hirudo lyophilized powder 0.6 g/kg treatment group (SM group); (4) Hirudo lyophilized powder 1.2 g/kg treatment group (SH group). Their fasting blood glucoses (FBG) were measured every 4 weeks. After treatment with Hirudo lyophilized powder at a corresponding dose once a day for 16 weeks, their metabolic and biochemical as well as oxidative stress parameters were tested, and the kidney weight (KW)/body weight (BW) was calculated. The renal tissues were used for histological, mRNA, and protein expression analysis. The results showed that Hirudo lyophilized powder could protect against the structural damages and functional changes of diabetic renal tissue by inhibiting oxidative stress, inflammation, and fibrosis. Furthermore, it was found in the further research that inhibiting the NOX4 expression and JAK2/STAT1/STAT3 pathway activation might be the underlying mechanisms. Collectively, Hirudo lyophilized powder might be a promising therapeutic agent for the treatment of DN.
Research on Fatigue Model of Semi‐Rigid Base Asphalt Pavement before and after Polymer Grouting
Authors: Zhang Bei , Zhang Xu , Zhong Yanhui , Li Xiaolong , Hao Meimei , Sang Xianwei , Wang Xiaoliang , Liu Jianyang
Published: February 2021

To improve the service life of a semirigid base asphalt pavement and prolong its service cycle, it is imperative to conduct long‐term performance research before and after pavement disease repair. This study proposes a fatigue damage model for pavement and polymer materials and uses the finite element method to establish a three‐dimensional numerical model of a semirigid base asphalt pavement structure. Moreover, it compares and analyzes the mechanical response and fatigue damage of this pavement before and after polymer repair. The evolution law is verified by indoor fatigue tests. The results show that, under a standard load of 0.7 MPa, the vertical displacement and the Mises stress of the vacant position after the polymer repair are reduced by 61% and 69%, respectively. Under a cyclic load of 1.2 MPa, the number of load actions increases from 500,000 to more than 5 million, and the fatigue damage factor of the polymer is reduced by 29%. With the increase in the number of fatigue test loads, the cumulative evolution trend of the fatigue damage is basically consistent with the results of the numerical simulation, which verifies the rationality of the numerical model. This research is relevant for providing a reference for extending the service life of expressways and improving the technical level of expressway maintenance.
Deep Residual Network in Network
Authors: Alaeddine Hmidi , Jihene Malek
Published: February 2021

Deep network in network (DNIN) model is an efficient instance and an important extension of the convolutional neural network (CNN) consisting of alternating convolutional layers and pooling layers. In this model, a multilayer perceptron (MLP), a nonlinear function, is exploited to replace the linear filter for convolution. Increasing the depth of DNIN can also help improve classification accuracy while its formation becomes more difficult, learning time gets slower, and accuracy becomes saturated and then degrades. This paper presents a new deep residual network in network (DrNIN) model that represents a deeper model of DNIN. This model represents an interesting architecture for on‐chip implementations on FPGAs. In fact, it can be applied to a variety of image recognition applications. This model has a homogeneous and multilength architecture with the hyperparameter “L” (“L” defines the model length). In this paper, we will apply the residual learning framework to DNIN and we will explicitly reformulate convolutional layers as residual learning functions to solve the vanishing gradient problem and facilitate and speed up the learning process. We will provide a comprehensive study showing that DrNIN models can gain accuracy from a significantly increased depth. On the CIFAR‐10 dataset, we evaluate the proposed models with a depth of up to L = 5 DrMLPconv layers, 1.66x deeper than DNIN. The experimental results demonstrate the efficiency of the proposed method and its role in providing the model with a greater capacity to represent features and thus leading to better recognition performance.
Advanced Direct Digital Synthesis Generator Design for Transuranic Nuclide Alpha Spectrometry Pulses
Authors: Peng Guili , Tuo Xianguo , Li Huailiang , Shi Rui
Published: February 2021

Alpha energy spectrum measurement has been employed in the nuclear waste disposal of transuranic nuclides (such as 239Pu and 241Am), supervision, and disposal process. The alpha spectrum is made up of alpha particles, which have a fast-moving helium nucleus and an energy of 4–8 MeV with weak penetration ability. Removing alpha particles from radioactive nuclides is an important scientific issue. In this study, a transuranic nuclide alpha particle pulse generator that produces simulated alpha particle pulses similar to real particles was designed. Field programmable gate array (FPGA) was adopted as its core chip and we obtained the digital pulse waveform using software tracing points while simulating real alpha particles by random numbers. Accordingly, the alpha energy spectrum of a radioactive source 241Am was obtained using a passivated ion-implanted planar silicon (PIPS) detector. Afterward, the alpha particle was extracted from the energy spectrum and was then compared to the alpha particle pulse of the two methods, deriving a result. Here, both groupings of particle pulse waveforms were found to be very similar, and the periodic error of the particle was observed to be less than 1%. Furthermore, the amplitude and time interval of the particle were apparently similar to the actual spectrometry pulse.
[Retracted] Protease‐Activated Receptor 1 Contributes to Microcirculation Failure and Tubular Damage in Renal Ischemia‐Reperfusion Injury in Mice
Authors: Guan Yu , Nakano Daisuke , Li Lei , Zheng Haofeng , Nishiyama Akira , Tian Ye , Zhang Lei
Published: February 2021

Ischemia‐reperfusion‐ (IR‐) induced kidney injury is difficult to avoid during renal transplantation and robot‐assisted partial nephrectomy. Renal IR injury is characterized by tubular damage, microcirculation failure, and inflammation, which coordinately augment renal injury; however, no specific treatment is available for these conditions. Protease‐activated receptor‐1 (PAR‐1) and its ligand, thrombin, are involved in coagulation and were shown to be associated with epithelial cell injury. Here, we hypothesized that PAR‐1 exaggerated renal IR‐induced tubular cell damage and microcirculation failure and that pharmacological inhibition of PAR‐1 by Q94 could prevent these injuries. Renal warm IR increased the expression of PAR‐1 in the renal tubules. Q94 attenuated renal IR‐induced changes and histopathological damage. Microcirculation failure analyzed by congestion in the histopathology and blood cell flow examined by intravital multiphoton microscopy were suppressed by Q94 treatment. Q94 also dramatically increased tubular cell proliferation despite the lower renal damage. Thrombin suppressed cell proliferation and induced apoptosis in the tubules; these effects were prevented by Q94 treatment. Taken together, PAR‐1 was associated with renal IR injury. Inhibition of PAR‐1 ameliorated injury possibly by improving renal microcirculation and tubular cell survival/proliferation.
Analysis of the Effect of Whirl on Drillstring Fatigue
Authors: Wang Chong , Li Xufeng , Li Yafeng , Xu Wenhao , Liao Wuyi
Published: February 2021

There are many kinds of vibration forms of drillstring in petroleum drilling. Whirl is one of the main vibration modes when drilling tools are drilling, and it is also the main reason of fatigue failure of the drillstring. In this paper, the causes of drillstring whirl are analyzed. The results show that the speed of rotation (RPM) is a major factor that affects the severity of the whirl. The greater the speed of rotation, the more intense the whirl. The whirl of the drillstring will produce bending stress. The severity of the whirl of the drillstring is the main factor affecting the bending stress. The increase of RPM and weight on bit (WOB) will lead to the increase of bending stress. The RPM has a great influence on the bending stress. Given the complex stress condition of drillstring, the calculation model of safety factor is established. The bending stress and safety factor are calculated under the different WOB and RPM. The relationship between dynamic bending stress and the safety factor of drilling tools is analyzed. Bending stress has great influence on the safety factor of drillstring. The variation trend of safety factor is opposite to that of bending stress caused by whirl. It provides a theoretical reference for the optimization of drilling tools in drilling engineering construction.
Self-Perception of Dental Esthetics among Dental Students at King Saud University and Their Desired Treatment
Authors: El Mourad Aminah M. , Al Shamrani Ahoud , Al Mohaimeed Maha , Al Sougi Sarah , Al Ghanem Shahad , Al Manie Wassan
Published: February 2021

Objective. Dental esthetic procedures are popular worldwide, and dentists are responsible for recommending several treatment options to their patients. To do this competently, dentists must have an educated opinion of their features. Therefore, we aimed to evaluate the self-perception of dental esthetics among male and female dental students and assess its effect on their desired treatment. Methodology. We conducted a questionnaire-based cross-sectional study involving 450 male and female dental students from five academic years with different grade point averages (GPAs) and monthly household incomes. The questionnaire comprised four sections. The subjects selected their teeth-color preferences using a commercial shade guide. The outcomes were presented using descriptive statistics and were compared with Pearson’s chi-square test. The level of statistical significance was set at a

p

-value of 0.05. Results. Female students (52%) showed a significantly higher preference for changing their tooth color (shade B1 was desired most often), whereas male students reported a higher need for orthodontic treatment and ceramic veneers (

p
<
0.0001

and

p
=
0.002

). Fifth-year students were more satisfied with their teeth color as compared with 1st-year students (

p
=
0.047

). High-GPA students showed significantly lower confidence regarding their smiles (

p
=
0.030

). A high percentage of students (39.1%) with household incomes of less than 10,000 SR preferred tooth-colored restorations. Conclusion. We concluded that the majority of dental students were confident about their smiles. Senior students were more satisfied with their teeth color, while younger students desired whiter teeth. Bleaching and orthodontics were the most desired treatment options.
Analyzing and Evaluating Smart Cities for IoT Based on Use Cases Using the Analytic Network Process
Authors: Huang Chao , Nazir Shah
Published: February 2021

With the passage of time, the world population is growing. Proper utilization of resources and other devices is tremendously playing an important role to easily examine, manage, and control the resources of the Internet of Things (IoT) in the smart city. Research in the field of IoT has revolutionized the services mostly in smart cities. In the smart city, the applications of IoT are utilized without human involvement. Diverse IoT devices are connected with each other and communicate for different tasks. With the existence of a huge number of IoT devices in the forthcoming years, the chances of privacy breach and information leakage are increasing. Billions of devices connected on IoT producing huge volume of data bound to cloud for processing, management, and storage. Sending of whole data to the cloud might create risk of security and privacy. Various needs of the smart city should be considered for both urgent and effective solutions to support requirements of the growing population. On the other side of rising technology, the IoT evolution has massively produced diverse research directions for the smart city. Keeping in view the use cases of the smart city, the proposed study presents the analytic network process (ANP) for evaluating smart cities. The approach of ANP works well in the situation of complexity, and vagueness exists among the available alternatives. The experimental results of the planned approach show that the approach is effective for evaluating the smart cities for IoT based on the use cases.
Algorithm of Strawberry Disease Recognition Based on Deep Convolutional Neural Network
Authors: Ma Li , Guo Xueliang , Zhao Shuke , Yin Doudou , Fu Yiyi , Duan Peiqi , Wang Bingbing , Zhang Li
Published: February 2021

The growth of strawberry will be stressed by biological or abiotic factors, which will cause a great threat to the yield and quality of strawberry, in which various strawberry diseased. However, the traditional identification methods have high misjudgment rate and poor real‐time performance. In today′s era of increasing demand for strawberry yield and quality, it is obvious that the traditional strawberry disease identification methods mainly rely on personal experience and naked eye observation and cannot meet the needs of people for strawberry disease identification and control. Therefore, it is necessary to find a more effective method to identify strawberry diseases efficiently and provide corresponding disease description and control methods. In this paper, based on the deep convolution neural network technology, the recognition of strawberry common diseases was studied, as well as a new method based on deep convolution neural network (DCNN) strawberry disease recognition algorithm, through the normal training of strawberry image feature representation in different scenes, and then through the application of transfer learning method, the strawberry disease image features are added to the training set, and finally the features are classified and recognized to achieve the goal of disease recognition. Moreover, attention mechanism and central damage function are introduced into the classical convolutional neural network to solve the problem that the information loss of key feature areas in the existing classification methods of convolutional neural network affects the classification effect, and further improves the accuracy of convolutional neural network in image classification.
Parallel Implementations of Candidate Solution Evaluation Algorithm for N‐Queens Problem
Authors: Cao Jianli , Chen Zhikui , Wang Yuxin , Guo He
Published: February 2021

The N‐Queens problem plays an important role in academic research and practical application. Heuristic algorithm is often used to solve variant 2 of the N‐Queens problem. In the process of solving, evaluation of the candidate solution, namely, fitness function, often occupies the vast majority of running time and becomes the key to improve speed. In this paper, three parallel schemes based on CPU and four parallel schemes based on GPU are proposed, and a serial scheme is implemented at the baseline. The experimental results show that, for a large‐scale N‐Queens problem, the coarse‐grained GPU scheme achieved a maximum 307‐fold speedup over a single‐threaded CPU counterpart in evaluating a candidate solution. When the coarse‐grained GPU scheme is applied to simulated annealing in solving N‐Queens problem variant 2 with a problem size no more than 3000, the speedup is up to 9.3.
Bearing Fault Diagnosis Based on Multiscale Convolutional Neural Network Using Data Augmentation
Authors: Han Seungmin , Oh Seokju , Jeong Jongpil
Published: February 2021

Bearings are one of the most important parts of a rotating machine. Bearing failure can lead to mechanical failure, financial loss, and even personal injury. In recent years, various deep learning techniques have been used to diagnose bearing faults in rotating machines. However, deep learning technology has a data imbalance problem because it requires huge amounts of data. To solve this problem, we used data augmentation techniques. In addition, Convolutional Neural Network, one of the deep learning models, is a method capable of performing feature learning without prior knowledge. However, since conventional fault diagnosis based on CNN can only extract single‐scale features, not only useful information may be lost but also domain shift problems may occur. In this paper, we proposed a Multiscale Convolutional Neural Network (MSCNN) to extract more powerful and differentiated features from raw signals. MSCNN can learn more powerful feature expression than conventional CNN through multiscale convolution operation and reduce the number of parameters and training time. The proposed model proved better results and validated the effectiveness of the model compared to 2D‐CNN and 1D‐CNN.
Mechanical and Acoustic Emission Responses of Rock Fragmentation under Disc Cutter Penetration
Authors: Liu Qi , Pan Yucong , Deng Penghai
Published: February 2021

To better understand the rock fragmentation mechanism and optimize cutter design and selection for rock excavation by TBM, a set of three‐dimensional indentation tests was conducted with different rock and cutter types. Acoustic emission (AE) monitoring technique was employed to capture the information of the rock damage evolution real‐timely. It is found that the penetration by using the constant cross section (CCS) cutter tends to induce inconspicuous rock chips formation before the sudden occurrence of the macrocrack, but that by using the V‐type cutter tends to induce gradual rock fragmentation accompanied by the multiple local rock chips formation and the sawtooth force‐penetration curve. Meanwhile, rock fragmentation models for CCS and V‐type cutters were compared, and the spatio‐temporal evolution of AE events was quantitatively analyzed to reflect the rock damage zone development process. Results indicate that the V‐type cutter has greater penetration ability and the CCS cutter can cause larger unit damage zone radius. Microscopic observation by using the scanning electron microscope (SEM) reveals that the fracture mechanism for the crushed zone of rock is mainly shear type and that for the major crack is tensile type. It does not matter with rock types or cutter types.
Seismic Behavior of Flexible Geogrid Wrap‐Reinforced Soil Slope
Authors: Huang Liang , He Weili , Hou Yujie , Liu Dun , Wang Bo , Zhu Jiahua , Wang Junjie
Published: February 2021

In this study, the failure mode of flexible reinforced soil slopes under earthquake action was investigated by shaking table tests. The distribution law of a potential failure surface of a flexible no‐faceplate reinforced soil slope under earthquake action was obtained based on the analysis results. A simplified trilinear failure surface suitable for flexible reinforced soil slopes without faceplate was proposed. Subsequently, based on the upper‐bound theorem of limit analysis, we derived the formula for calculating the yield seismic acceleration coefficient of a flexible no‐faceplate reinforced soil slope under a seismic load. The main parameters that affect its seismic performance were determined. The flexible geogrid reverse‐packed reinforced earth structure can effectively limit the fracture of a slope body and improve the stability of the slope. This provides a theoretical basis for facilitating the engineering of flexible reinforced soil slopes.
Computational FEM Model and Phantom Validation of Microwave Ablation for Segmental Microcalcifications in Breasts Using a Coaxial Double‐Slot Antenna
Authors: Segura Félix Kristian , Guerrero López Geshel D. , Cepeda Rubio Mario F. J. , Hernández Jacquez José I. , Flores García Francisco G. , Hernández Arturo Vera , Salas Lorenzo Leija , Orozco Ruiz de la Peña Eva C.
Published: February 2021

Introduction. Cancer is the second leading cause of death worldwide. Breast cancer is the second most common cause of cancer‐related mortality, accounting for 11.6% of the total number of deaths. The main treatments for this disease are surgical removal of the tumor, radiotherapy, and chemotherapy. Recently, different minimally invasive technologies have been applied (e.g., emission of electromagnetic waves, thermal and chemical means) to overcome the important side effects of these treatment modalities. The objective of this study was to develop and evaluate a predictive computational model of microwave ablation. Materials and Methods. The predictive computational model of microwave ablation was constructed by means of a dual‐slot coaxial antenna. The model was compared with an experiment performed using a breast phantom, which emulates the dielectric properties of breast tissue with segmental microcalcifications. The standing wave ratio (SWR) was obtained for both methods to make a comparison and determine the feasibility of applying electromagnetic ablation to premalignant lesions in breasts. Specifically, for the analysis of segmental microcalcifications, a breast phantom with segmental microcalcifications was developed and two computational models were performed under the same conditions (except for blood perfusion, which was excluded in one of the models). Results. The SWR was obtained by triplicate experiments in the phantom, and the measurements had a difference of 0.191 between the minimum and maximum SWR values, implying a change of power reflection of 0.8%. The average of the three measurements was compared with the simulation that did not consider blood perfusion. The comparison yielded a change of 0.104, representing a 0.2% change in power reflection. Discussion. Both experimentation in phantom and simulations demonstrated that ablation therapy can be performed using this antenna. However, an additional optimization procedure is warranted to increase the efficiency of the antenna.
Modified Whale Optimization Algorithm for Solar Cell and PV Module Parameter Identification
Authors: Ye Xiaojia , Liu Wei , Li Hong , Wang Mingjing , Chi Chen , Liang Guoxi , Chen Huiling , Huang Hailong
Published: February 2021

The whale optimization algorithm (WOA) is a powerful swarm intelligence method which has been widely used in various fields such as parameter identification of solar cells and PV modules. In order to better balance the exploration and exploitation of WOA, we propose a novel modified WOA (MWOA) in which both the mutation strategy based on Levy flight and a local search mechanism of pattern search are introduced. On the one hand, Levy flight can make the algorithm get rid of the local optimum and avoid stagnation; thus, it is able to prevent the algorithm from losing diversity and to increase the global search capability. On the other hand, pattern search, a direct search method, has not only high convergence rate but also good stability, which can boost the local optimization ability of the WOA. Therefore, the combination of these two mechanisms can greatly improve the capability of WOA to obtain the best solution. In addition, MWOA may be employed to estimate parameters in single diode model (SDM), double diode model (DDM), and PV modules and to identify unknown parameters of two different types of PV modules under diverse light irradiance and temperature conditions. The analytical results demonstrate the validity and the practicality of MWOA for estimating parameters of solar cells and PV modules.
Microstructure Characteristics and Corrosion Resistance of Friction Stir Welded 2205 Duplex Stainless Steel
Authors: Zhao Yunqiang , Dong Chunlin , Jia Zhongxue , You Jiaqing , Tan Jinhong , Miao Shu , Yi Yaoyong
Published: February 2021

In this study, 2205 duplex stainless steel was friction‐stir‐welded at different welding speeds. The microstructural characteristics such as grain sizes, grain boundary misorientation angles, and phase contents in the stir zones of the joints were detected. The potentiodynamic polarization and electrochemical impedance spectroscopy were also measured to evaluate the corrosion property of the stir zones. The effects of the microstructures on the corrosion property for friction‐stir‐welded 2205 duplex stainless steel were analyzed. The results indicated that the FSW process refined the grains and increased the ferrite contents in the stir zones. With increasing the welding speed from 30 mm/min to 50 mm/min, the grain size in the stir zone decreased from 1.64 μm to 0.96 μm, the ferrite content decreased from 59% to 54.4%, and the fractions of low angle grain boundaries for austenite and ferrite phases decreased from 63.9% and 92.6% to 18.0% and 41.1%, respectively. In this study, the effect of grain size on the corrosion resistance was the most significant and it was followed by the phase composition and the grain boundary misorientation angle. The stir zone obtained at 50 mm/min has the highest corrosion resistance, and it is followed by the base material and the stir zone obtained at 30 mm/min.
A Five-Year Trend of Intestinal Parasite Prevalence among Students Attending Clinic at University of Gondar, Northwest Ethiopia
Authors: Derso Adane , Yenealem Gizachew , Addisu Ayenew
Published: February 2021

Background. Intestinal parasitic infections are the cause of the highest worldwide infectious disease and the major public health problems in developing countries. Among the cases, children and younger age are at high risk and the major victims. The aim of this study was to assess the five-year trend of intestinal parasite prevalence among University of Gondar students. Method. A retrospective cross-sectional study was conducted to assess the trend of intestinal parasite prevalence among students at the University of Gondar. The data was collected from students who have studied at the University of Gondar from 2014 to 2018 and who visited the student’s clinic and had recorded results of stool sample diagnosis on the laboratory logbook. Stool specimens were examined using direct saline wet mount methods. The data was analyzed by using SPSS version 20 software, and

P

value < 0.05 was considered as statistically significant. Moreover, chi-square was used to assess the association of different variables. Result. During the study period, a total of 6244 stool samples were requested for intestinal parasite diagnosis and it was found that 2850 specimens were positive for intestinal parasites, representing an overall prevalence of 45.6% with a fluctuating trend. Ten different parasites were reported with Entamoeba histolytica/dispar (20.3%) and Giardia lamblia (8.2%), the most frequently detected intestinal parasites. The prevalence of intestinal parasitic infections was higher in males (35.4%) than females (10.2%) (

P
=
0.02

). Conclusions. Intestinal parasitic infection was highly prevalent, and there were fluctuations in the prevalence of intestinal parasites from 2014 to 2018. Environmental sanitation improvement and health education schemes at the University of Gondar can be considered quite indispensable for the prevention and control of parasitic infections in the area.
Cytoplasmic Localization of Prostate-Specific Membrane Antigen Inhibitors May Confer Advantages for Targeted Cancer Therapies
Authors: Matthias Jessica , Engelhardt Johann , Schäfer Martin , Bauder-Wüst Ulrike , Meyer Philipp T. , Haberkorn Uwe , Eder Matthias , Kopka Klaus , Hell Stefan W. , Eder Ann-Christin
Published: February 2021

Targeted imaging and therapy approaches based on novel prostate-specific membrane antigen (PSMA) inhibitors have fundamentally changed the treatment regimen of prostate cancer. However, the exact mechanism of PSMA inhibitor internalization has not yet been studied, and the inhibitors' subcellular fate remains elusive. Here, we investigated the intracellular distribution of peptidomimetic PSMA inhibitors and of PSMA itself by stimulated emission depletion (STED) nanoscopy, applying a novel nonstandard live cell staining protocol. Imaging analysis confirmed PSMA cluster formation at the cell surface of prostate cancer cells and clathrin-dependent endocytosis of PSMA inhibitors. Following the endosomal pathway, PSMA inhibitors accumulated in prostate cancer cells at clinically relevant time points. In contrast with PSMA itself, PSMA inhibitors were found to eventually distribute homogeneously in the cytoplasm, a molecular condition that promises benefits for treatment as cytoplasmic and in particular perinuclear enrichment of the radionuclide carriers may better facilitate the radiation-mediated damage of cancerous cells. This study is the first to reveal the subcellular fate of PSMA/PSMA inhibitor complexes at the nanoscale and aims to inspire the development of new approaches in the field of prostate cancer research, diagnostics, and therapeutics.

Significance:

This study uses STED fluorescence microscopy to reveal the subcellular fate of PSMA/PSMA inhibitor complexes near the molecular level, providing insights of great clinical interest and suggestive of advantageous targeted therapies.
Sex Hormones, Insulin, and Insulin-like Growth Factors in Recurrence of High-Stage Endometrial Cancer
Authors: Merritt Melissa A. , Strickler Howard D. , Hutson Alan D. , Einstein Mark H. , Rohan Thomas E. , Xue Xiaonan , Sherman Mark E. , Brinton Louise A. , Yu Herbert , Miller David S. , Ramirez Nilsa C. , Lankes Heather A. , Birrer Michael J. , Huang Gloria S. , Gunter Marc J.
Published: February 2021

Background:

The influence of sex hormone and insulin/insulin-like growth factor (IGF) axis signaling on endometrial cancer recurrence is unknown. We evaluated these pathways in a prospective cohort of Gynecologic Oncology Group (GOG)0210 trial endometrial adenocarcinoma patients.

Methods:

Stage II–IV patients (N = 816) were included in this study. Pretreatment specimens were tested for tumor mRNA and protein expression of IGF1, IGF2, IGF-binding proteins (IGFBP)-1 and -3, insulin (IR) and IGF-I receptors (IGF1R), phosphorylated IR/IGF1R (pIGF1R/pIR), and estrogen (ER) and progesterone receptors (PR) using qPCR and IHC. Serum concentrations of insulin, IGF-I, IGFBP-3, estradiol, estrone, and sex hormone binding globulin were measured. HRs and 95% confidence intervals (CI) for progression-free survival were calculated from Cox models adjusting for age, stage, and grade.

Results:

Recurrence occurred in 280 (34%) cases during a median of 4.6 years of follow-up. ER positivity (HR, 0.67; 95% CI, 0.47–0.95), IR positivity (HR, 0.53; 95% CI, 0.29–0.98), and circulating IGF-I (highest vs. lowest quartile: HR, 0.66; 95% CI, 0.47–0.92) were inversely associated with recurrence risk. Circulating estradiol (highest vs. lowest tertile: HR, 1.55; 95% CI, 1.02–2.36) and pIGF1R/pIR positivity (HR, 1.40; 95% CI, 1.02–1.92) were associated with increased recurrence risk.

Conclusions:

Circulating estradiol and tumor tissue phosphorylated (activated) IGR1R/IR were independently associated with higher risk of recurrence in patients with endometrial cancer.

Impact:

This study may inform future clinical trials of endocrine-targeted adjuvant therapies in patients with endometrial cancer that could include baseline assessment of serum and tissue biomarkers of estradiol and insulin signaling pathways.
Molecular Features of Cancer-associated Fibroblast Subtypes and their Implication on Cancer Pathogenesis, Prognosis, and Immunotherapy Resistance
Authors: Galbo Phillip M. , Zang Xingxing , Zheng Deyou
Published: February 2021

Purpose:

Cancer-associated fibroblasts (CAFs) are an important component of the tumor microenvironment, but a systematic investigation of their molecular characteristics and clinical relevance are lacking. Here, we sought to compare CAFs across multiple cancer types to identify critical molecular pathways activated in CAF subtypes, which may contribute to clinical outcome, disease progression, and immunotherapy resistance.

Experimental Design:

We performed integrated analysis of CAFs from melanoma, head and neck squamous cell carcinoma, and lung cancer, and identified the molecular characteristics that are distinctly active in each CAF subtype. Gene signatures for individual CAF subtypes were identified and used to study the association of subtype abundance with clinical outcome and immunotherapy resistance.

Results:

We identified six CAF subtypes (pan-CAF) shared across cancer types and uncovered the molecular characteristics and genetic pathways distinguishing them. Interestingly, these CAF subtypes express distinct immunosuppressive factors, such as CXCL12 and CXLC14, and stem cell–promoting factor IL6. In addition, we identified novel transcriptional drivers (MEF2C, TWIST1, NR1H3, RELB, and FOXM1) key to CAF heterogeneity. Furthermore, we showed that CAF subtypes were associated with different clinical outcomes and uncovered key molecular pathways that could activate or suppress cancer progression or were involved in resistance to anti-PD1 or anti–PD-L1 immunotherapy.

Conclusions:

Our study identifies the molecular characteristics of CAF subtypes shared across several cancer types, implicates cancer types that may benefit from CAF subtype targeted therapies, and identifies specific CAF subtypes associated with immunotherapy resistance.
Diagnostic Performance of 18F-DCFPyL-PET/CT in Men with Biochemically Recurrent Prostate Cancer: Results from the CONDOR Phase III, Multicenter Study
Authors: Morris Michael J. , Rowe Steven P. , Gorin Michael A. , Saperstein Lawrence , Pouliot Frédéric , Josephson David , Wong Jeffrey Y.C. , Pantel Austin R. , Cho Steve Y. , Gage Kenneth L. , Piert Morand , Iagaru Andrei , Pollard Janet H. , Wong Vivien , Jensen Jessica , Lin Tess , Stambler Nancy , Carroll Peter R. , Siegel Barry A.
Published: February 2021

Purpose:

Current FDA-approved imaging modalities are inadequate for localizing prostate cancer biochemical recurrence (BCR). 18F-DCFPyL is a highly selective, small-molecule prostate-specific membrane antigen–targeted PET radiotracer. CONDOR was a prospective study designed to determine the performance of 18F-DCFPyL-PET/CT in patients with BCR and uninformative standard imaging.

Experimental Design:

Men with rising PSA ≥0.2 ng/mL after prostatectomy or ≥2 ng/mL above nadir after radiotherapy were eligible. The primary endpoint was correct localization rate (CLR), defined as positive predictive value with an additional requirement of anatomic lesion colocalization between 18F-DCFPyL-PET/CT and a composite standard of truth (SOT). The SOT consisted of, in descending priority (i) histopathology, (ii) subsequent correlative imaging findings, or (iii) post-radiation PSA response. The trial was considered a success if the lower bound of the 95% confidence interval (CI) for CLR exceeded 20% for two of three 18F-DCFPyL-PET/CT readers. Secondary endpoints included change in intended management and safety.

Results:

A total of 208 men with a median baseline PSA of 0.8 ng/mL (range: 0.2–98.4 ng/mL) underwent 18F-DCFPyL-PET/CT. The CLR was 84.8%–87.0% (lower bound of 95% CI: 77.8–80.4). A total of 63.9% of evaluable patients had a change in intended management after 18F-DCFPyL-PET/CT. The disease detection rate was 59% to 66% (at least one lesion detected per patient by 18F-DCFPyL-PET/CT by central readers).

Conclusions:

Performance of 18F-DCFPyL-PET/CT achieved the study’s primary endpoint, demonstrating disease localization in the setting of negative standard imaging and providing clinically meaningful and actionable information. These data further support the utility of 18F-DCFPyL-PET/CT to localize disease in men with recurrent prostate cancer.

See related commentary by True and Chen, p. 3512
Improved hybrid algorithm based on GA and local search method for asymmetrical 9-level inverter
Authors: Feyrouz Abdelgoui Rim , Taleb Rachid , Bentaallah Abderrahim , Chabni Fayçal
Published: February 2021

Selective Harmonic elimination has emerged as an in-depth research method to replace traditional PWM technology. This study demonstrates the selective harmonic elimination by using a hybrid Genetic algorithm GA and local search (GA-LS) method of a uniform asymmetric multilevel inverter called USAMI That removes the higher-order harmonics defined while maintaining the fundamental voltage needed. This new technology can be implemented at any USAMI level. For example, in this article, we plan to use USAMI at 9 levels and find the optimal switching angle to remove the 5th, 7th, and 11th harmonics. 
A fuzzy-PID controller in shell and tube heat exchanger simulation modeled for temperature control
Authors: Somasundar Reddy C. , Balaji K.
Published: February 2021

Shell and tube heat exchanger is the most generally utilized types of heat exchanger for heat transfer in many industrial purposes. Shell and tube heat exchanger comprises a set of unit. One unit includes mechanical parts and another unit consists of controlling part. Both the unit has to be modelled to ensure the efficient operation of shell and tube heat exchanger. The mechanical modelling is completely established on the type of applications. The controller modelling is independent of the kind of applications. The controller only needs the input fluid and output fluid properties such as temperature and flow rate.  Hence the primary objective of the paper is to focus on the controller part for enhancing the heat exchanger performance. This paper proposes the novel fuzzy-PID controlling technique based on the multiplication operation to make the settling time and overshoot of setpoint temperature to be less to a greater extent and the results are compared with the conventional PI method with various tuning algorithms.
Real time face recognition of video surveillance system using haar cascade classifier
Authors: Ahmad Adlan Hakim , Saon Sharifah , Mahamad Abd Kadir , Darujati Cahyo , Mudjanarko Sri Wiwoho , Susiki Nugroho Supeno Mardi , Hariadi Mochamad
Published: February 2021

This project investigates the use of face recognition for a surveillance system. The normal video surveillance system uses in closed-circuit television (CCTV) to record video for security purpose. It is used to identify the identity of a person through their appearances on the recorded video, manually. Today’s video surveillance camera system usually not occupied with a face recognition system. With some modification, a surveillance camera system can be used as face detection and recognition that can be done in real-time. The proposed system makes use of surveillance camera system that can identify the identity of a person automatically by using face recognition of Haar cascade classifier. The hardware used for this project were Raspberry Pi as a processor and Pi Camera as a camera module. The development of this project consist of three main phases which were data gathering, training recognizer, and face recognition process. All three phases have been executed using Python programming and OpenCV library, which have been performed in a Raspbian operation system. From the result, the proposed system successfully displays the output result of human face recognition, with facial angle within ±40°, in medium and normal light condition, and within a distance of 0.4 to 1.2 meter. Targeted image are allowed to wear face accessory as long as not covering the face structure. In conclusion, this system considered, can reduce the cost of manpower in order to identify the identity of a person in real time situation.
A novel image encryption scheme based on DCT transform and DNA sequence
Authors: A. Yassin Ali , Mohammed Rashid Abdullah , J. Yassin Abdulla , Alasadi Hamid
Published: February 2021

Recently, the concept of DNA has been invested in computing technology in different ways which linking information technology and biological sciences. There are several encryption algorithms based on DNA encoding that has been proposed, which leads to generating a new direction in image encryption. However, the DNA encryption scheme has drawbacks such as expensive experimental equipment, difficult operations, and hard to hold its biotechnology. Additionally, during careful cryptanalysis that applied to most of these image encryption schemes, we notice that DNA operators can only influence one DNA base, which causes poor diffusion. Our proposed scheme is not applied complex biological operation but just is given to improve the diffusion ability of image encryption scheme by using DNA sequence and DCT transform. Our works overcome above-aforementioned issues. Furthermore, empirical results on real images and security analysis demonstrate that our proposed scheme not only has flexibility and efficiency encryption scheme but also has the ability to resist well-known attacks such as entropy attack, differential attack, statistical attack, chosen/known plain image attack. Additionally, our work enjoys several strong characteristics as follows: (1) the decryption error is very low to recover the original image; (2) Once key for each encryption process and if the user wants to use the same key in many times, our proposed scheme supports secret key sensitivity; (3) the value of correlation of the encrypted image is null; (4) the scrambling process is good and generate high disorder at the output. As a result, our proposed scheme achieves a good balance between strong security and high performance.
Optimized and efficient deblurring through constraint conditional modelling
Authors: H C Ravikumar , Karthik P
Published: February 2021

Image deburring technique refers to restoring an image from the degraded version named blurred. Blurring can be caused due to various phenomena such as optical system, motion blur and other phenomena. Moreover, to deblur the image it is essential to know the blurring process characteristics and it is one of the difficult task. In past several deblurring algorithm have been proposed to approximate the kernel blur, however they lack the efficiency and expensive to be applied for the real world scenario. In this paper, we have proposed a CCM (constraint conditional model) to deblur the image; it learns the direct mapping from the degraded to the absolute clean image. Moreover, the main aim of CCM is to restore the image in its original form, the best advantage of CCM is that it provides handsome tradeoff between the image quality and efficiency. Moreover CCM is evaluated on the three different standard datasets by considering the different performance metrics and through the comparison analysis observation has made that CCM approach outperforms the other techniques.