bluuebunny/crossref_metadata_2025 huggingface dataset:
Poor clinical outcome despite successful basilar occlusion recanalization in the early time window: incidence and predictors
Authors: Pop Raoul , Finitsis Stephanos Nikolaos , Arquizan Caroline , Elhorany Mahmoud , Naggara Olivier , Darcourt Jean , Clarençon Frédéric , Richard Sébastien , Marnat Gaultier , Bourcier Romain , Sibon Igor , Dargazanli Cyril , Blanc Raphaël , Lapergue Bertrand , Consoli Arturo , Eugene Francois , Vannier Stephane , Caroff Jildaz , Denier Christian , Boulanger Marion , Gauberti Maxime , Rouchaud Aymeric , Macian Francisco , Rosso Charlotte , Turc Guillaume , Ozkul-Wermester Ozlem , Albucher Jean François , Le Bras Anthony , Evain Sarah , Wolff Valerie , Timsit Serge , Gentric Jean-Christophe , Bourdain Frédéric , Veunac Louis , Papagiannaki Chrysanthi , Gory Benjamin
Published: April 2022

Background

Endovascular treatment (EVT) for basilar artery occlusions (BAO) is associated with a higher rate of futile recanalization compared with anterior circulation procedures. We aimed to identify the incidence and predictors of poor clinical outcome despite successful reperfusion in current clinical practice.

Methods

We used data from the ETIS (Endovascular Treatment in Ischemic Stroke) registry, a prospective multicenter observational registry of stroke treated with EVT in France. Patients undergoing EVT for acute BAO from January 2014 to May 2019 successfully treated within 8 hours from onset were included. Predictors of 90-day poor outcome (modified Rankin Scale (mRS) 4–6) were researched within patients with successful (modified Thrombolysis In Cerebral Infarction (mTICI 2b-3)) and excellent (mTICI 2c-3) reperfusion.

Results

Among 242 patients treated within 8 hours, successful reperfusion was achieved in 195 (80.5%) and excellent reperfusion in 120 (49.5%). Poor outcome was observed in 107 (54.8%) and 60 (50%) patients, respectively. In patients with successful early reperfusion, age, higher initial National Institutes of Health Stroke Scale (NIHSS) score, lower posterior circulation Alberta Stroke Programme Early CT Score (pc-ASPECTS), and absence of prior intravenous thrombolysis were independent predictors of poor outcome. The only treatment factor with an independent predictive value was first-pass mTICI 2b-3 reperfusion (adjusted OR 0.13, 95% CI 0.05 to 0.37, p<0.001). In patients with excellent early reperfusion, independent predictors were age, initial NIHSS score, first-pass mTICI 2c-3 reperfusion, and hemorrhagic transformation on post-interventional imaging.

Conclusions

Early successful reperfusion with EVT occurred in 80.5% of patients, and the only treatment-related factor predictive of clinical outcome was first pass mTICI 2b-3 reperfusion. Further research is warranted to identify the optimal techniques and devices associated with first pass reperfusion in the posterior circulation.
Determinants of cerebral aneurysm occlusion after embolization with the WEB device: a single-institution series of 215 cases with angiographic follow-up
Authors: Cortese Jonathan , Caroff Jildaz , Chalumeau Vanessa , Gallas Sophie , Ikka Léon , Moret Jacques , Sabuzi Federico , Popescu Septimiu Daniel , Ozanne Augustin , Grimaldi Lamiae , Mihalea Cristian , Spelle Laurent
Published: April 2022

Background

Woven EndoBridge (WEB) devices are becoming a reliable option for the treatment of wide-neck bifurcation aneurysms, but clear predictive factors are still missing to understand the one in five aneurysm remnant rate.

Objective

To evaluate occlusion outcomes after WEB treatment to identify potential determinants of aneurysm occlusion.

Methods

A single-center database with consecutive aneurysms treated with WEB between July 2012 and October 2021 was reviewed for potential determinants of aneurysm adequate occlusion (defined as a Bicêtre Occlusion Scale Score (BOSS) of 0, 0’, 1 or 2), through univariate and multivariable analysis. Patients without angiographic follow-up were excluded.

Results

215 of 247 individual aneurysms were included in the final analysis, of which 59 (27%) were ruptured. Mean age of patients was 56 years (range 23–90 years) and 65% were female. Mean angiographic follow-up was at 18 months (range 3–97 months). Adequate and complete occlusion were achieved in 171/215 (79.5%) and 135/215 (62.8%) of cases, respectively. Aneurysm irregular shape (aOR=0.42, 95% CI 0.20 to 0.88; p=0.02), aneurysm height (aOR=0.79, 95% CI 0.66 to 0.94; p<0.01), and WEB shape modification (aOR=0.98, 95% CI 0.97 to 1.00; p=0.02) were all independent predictors of aneurysm recurrence, whereas the WEB oversizing ratio (WEB width/aneurysm mean width) (aOR=16.4, 95% CI 1.4 to 266.7; p=0.04) was an independent predictor of adequate occlusion.

Conclusion

In this study we demonstrated that a width oversizing strategy of the WEB device was an independent predictor of aneurysm angiographic occlusion. Conversely, aneurysm height, irregular aneurysm, and WEB shape modification were all independent determinants of angiographic aneurysm remnant. These results may help to select aneurysms suitable for the WEB device and WEB sizing.
Pneumomediastinum in patients with COVID-19 undergoing CT pulmonary angiography: a retrospective cohort study
Authors: Baslas Rohit , Condurache Dorina-Gabriela , Jayal Ambikesh , Colquhoun Matthew , de Wolff Jacob Frederik
Published: April 2022

Background

Various complications have been reported in patients with COVID-19 including pneumomediastinum.

Methods

The primary objective of the study was to determine the incidence of pneumomediastinum in COVID-19 positive patients who underwent CT pulmonary angiography (CTPA). The secondary objectives were to analyse if the incidence of pneumomediastinum changed between March and May 2020 (peak of the first wave in the UK) and January 2021 (peak of the second wave in the UK) and to determine the mortality rate in patients with pneumomediastinum. We undertook an observational, retrospective, single-centre, cohort study of patients with COVID-19 admitted to Northwick Park Hospital.

Results

74 patients in the first wave and 220 patients in the second wave met the study criteria. Two patients during the first wave and eleven patients during the second wave developed pneumomediastinum.

Conclusions

The incidence of pneumomediastinum changed from 2.7% during the first wave to 5% during the second wave and this change was not statistically significant (p value 0.4057). The difference in mortality rates of patients with pneumomediastinum in both waves of COVID-19 (69.23%) versus patients without pneumomediastinum in both waves of COVID-19 (25.62%) was statistically significant (p value 0.0005). Many patients with pneumomediastinum were ventilated, which could be a confounding factor. When controlling for ventilation, there was no statistically significant difference in the mortality rates of ventilated patients with pneumomediastinum (81.81%) versus ventilated patients without pneumomediastinum (59.30%) (p value 0.14).
A multi-institutional prospective observational study to evaluate fascia iliaca compartment block (FICB) for preventing delirium in adults with hip fracture
Authors: Salottolo Kristin , Meinig Richard , Fine Landon , Kelly Michael , Madayag Robert , Ekengren Francie , Tanner Allen , Roman Phillip , Bar-Or David
Published: April 2022

Objectives

Until recently, systemic opioids have been standard care for acute pain management of geriatric hip fracture; however, opioids increase risk for delirium. Fascia Iliaca compartment blocks (FICB) may be favored to systemic analgesia for reducing delirium, but this has not been well demonstrated. We evaluated the efficacy of adjunctive FICB versus systemic analgesia on delirium incidence, opioid consumption, and pain scores.

Methods

This prospective, observational cohort study was performed in patients (55–90 years) with traumatic hip fracture admitted to five trauma centers within 12 hours of injury, enrolled between January 2019 and November 2020. The primary end point was development of delirium, defined by the Confusion Assessment Method tool, from arrival through 48 hours postoperatively, and analyzed with multivariate Firth logistic regression. Secondary end points were analyzed with analysis of covariance models and included preoperative and postoperative oral morphine equivalents and pain numeric rating scale scores.

Results

There were 517 patients enrolled, 381 (74%) received FICB and 136 (26%) did not. Delirium incidence was 5.4% (n=28) and was similar for patients receiving FICB versus no FICB (FICB, 5.8% and no FICB, 4.4%; adjusted OR: 1.2 (95% CI 0.5 to 3.0), p=0.65). Opioid requirements were similar for patients receiving FICB and no FICB, preoperatively (p=0.75) and postoperatively (p=0.51). Pain scores were significantly lower with FICB than no FICB, preoperatively (4.2 vs 5.1, p=0.002) and postoperatively (2.9 vs 3.5, p=0.04).

Conclusions

FICB demonstrated significant benefit on self-reported pain but without a concomitant reduction in opioid consumption. Regarding delirium incidence, these findings suggest clinical equipoise and the need for a randomized trial.

Level of evidence

II—prospective, therapeutic.
Superionic Lithium Argyrodite Electrolytes by Bromine-Doping for All-Solid-State Lithium Batteries
Authors: Zhang Zhichao , Tian Yongtao , Liu Gaozhan , Wu Ming , He Hao , Yao Xiayin
Published: April 2022

High energy density all-solid-state rechargeable batteries with excellent safety are considered as reliable alternative to the current lithium-ion battery. The major challenge of all-solid-state rechargeable batteries is to develop new electrolyte material with high conductivity and good stability against lithium. In this work, the argyrodite electrolytes Li5.4PS4.4Cl1.6−x
Br
x
(0 ≤ x ≤ 0.8) are synthesized through wet-milling method. Benefit from higher concentration of Br and the lattice softening of crystal structure, Li5.4PS4.4Cl1.2Br0.4 electrolyte with the highest lithium ion conductivity of 8.17 mS cm−1 is realized. The Li/Li5.4PS4.4Cl1.2Br0.4/Li symmetric battery can stable cycle for 2500 h at 0.1 mA cm−2, showing favorable stability against lithium. The assembled LiCoO2/Li5.4PS4.4Cl1.2Br0.4/Li battery delivers an initial reversible capacity of 122.4 mAh g−1 with a capacity retention of 82.8% after 100 cycles. These results demonstrate a promising argyrodite electrolyte Li5.4PS4.4Cl1.2Br0.4 with high ionic conductivity and favorable electrochemical stability for all-solid-state lithium battery.
Conceptual Circuit Model for the Prediction of Electrochemical Performance of Carbonaceous Electrodes Containing Reduced Ultra Large Graphene Oxide
Authors: Madani Sara , Falamaki Cavus , Kazemzadeh Mehdi , Rahmanifard Ali , Aboutalebi Seyed Hamed
Published: April 2022

A concneptual model based on the physics of electrode components has been proposed for the prediction of the electrochemical behavior of carbonaceous electrode composites containing reduced ultra large graphene oxide (RUGO). RUGO has been used as one of the main components of capacitive deionization (CDI) electrode composites including activated carbon (AC) and carbon nanotubes (CNT). An optimal composition of the CDI electrode materials was determined that resulted in a high ion adsorption capacity of 10.51 mg g−1 @ 1.1 V in the absence of pseudo-capacitive materials. Using small amounts of RUGO (total RUGO and CNT’s content less than 10 wt%) in the CDI electrodes led to relatively high electrochemical capacitance and ion adsorption capacity. The electrochemical impedance spectroscopy and CDI experiments were in reasonable accordance with the mathematical model results.
Universal Correlation between Cathode Roughness Factor and H2/Air Performance Losses in Voltage Cycling-Based Accelerated Stress Tests
Authors: Della Bella Roberta K. F. , Stühmeier Björn M. , Gasteiger Hubert A.
Published: April 2022

The loss of electrochemically active surface area (ECSA) in the cathode during load cycling remains a major durability issue for proton exchange membrane fuel cells (PEMFCs). Here, the degradation of low-loaded cathodes (0.1

mg

Pt

cm

MEA

−
2

) was investigated by accelerated stress tests (ASTs) in H2/N2 configuration, varying the upper potential limit (UPL, 0.85–1.0 V) and the hold time (1, 2, or 8 s) of the square wave voltage cycling profiles. A full voltage loss analysis was performed at beginning-of-life and after 100, 300, 1 k, 2 k, 5 k, 10 k, 20 k, 50 k, 100 k, 200 k, and 500 k cycles, determining: (i) the roughness factor (rf) via CO-stripping; (ii) the H2-crossover; (iii) the cathode electrode’s proton conduction resistance; (iv) the H2/O2 and H2/air performance; and, (v) the O2 transport resistance. It was found that the ECSA/rf deteriorates linearly vs the logarithm of the number of cycles or time at UPL, with higher slopes for harsher ASTs. The individual voltage losses were found to be either unaffected by the aging (H2-crossover and proton conduction resistance) or depend exclusively on the cathode rf (mass/specific activity and O2 transport resistances), independent of the AST procedure. This results in a universal correlation between H2/air performance and rf during voltage cycling ASTs.
The Modulation of Interferon Regulatory Factor-1 via Caspase-1-Mediated Alveolar Macrophage Pyroptosis in Ventilator-Induced Lung Injury
Authors: Dai Minhui , Li Qian , Pan Pinhua
Published: April 2022

Background. To examine the role of interferon regulatory factor-1 (IRF-1) and to explore the potential molecular mechanism in ventilator-induced lung injury. Methods. Wild-type C57BL/6 mice and IRF-1 gene knockout mice/caspase-1 knockout mice were mechanically ventilated with a high tidal volume to establish a ventilator-related lung injury model. The supernatant of the alveolar lavage solution and the lung tissues of these mice were collected. The degree of lung injury was examined by hematoxylin and eosin staining. The protein and mRNA expression levels of IRF-1, caspase-1 (p10), and interleukin (IL)-1β (p17) in lung tissues were measured by western blot and quantitative real-time polymerase chain reaction, respectively. Pyroptosis of alveolar macrophages was detected by flow cytometry and western blotting for active caspase-1 and cleaved GSDMD. An enzyme-linked immunosorbent assay was used to measure the levels of IL-1β, IL-18, IL-6, TNF-α, and high mobility group box protein 1 (HMGB-1) in alveolar lavage fluid. Results. IRF-1 expression and caspase-1-dependent pyroptosis in lung tissues of wild-type mice were significantly upregulated after mechanical ventilation with a high tidal volume. The degree of ventilator-related lung injury in IRF-1 gene knockout mice and caspase-1 knockout mice was significantly improved compared to that in wild-type mice, and the levels of GSDMD, IL-1β, IL-18, IL-6, and HMGB-1 in alveolar lavage solution were significantly reduced (P<0.05). The expression levels of caspase-1 (p10), cleaved GSDMD, and IL-1β (p17) proteins in lung tissues of IRF-1 knockout mice with ventilator-related lung injury were significantly lower than those of wild-type mice, and the level of pyroptosis of macrophages in alveolar lavage solution was significantly reduced. Conclusions. IRF-1 may aggravate ventilator-induced lung injury by regulating the activation of caspase-1 and the focal death of alveolar macrophages.
Integrated Bioinformatics Analysis and Verification of Gene Targets for Myocardial Ischemia-Reperfusion Injury
Authors: Wang Jianru , Li Xiaohui , Peng Guangcao , Fan Genhao , Zhang Mengmeng , Chen Jian
Published: April 2022

Background. Myocardial ischemia-reperfusion injury (MIRI) has become a thorny and unsolved clinical problem. The pathological mechanisms of MIRI are intricate and unclear, so it is of great significance to explore potential hub genes and search for some natural products that exhibit potential therapeutic efficacy on MIRI via targeting the hub genes. Methods. First, the differential expression genes (DEGs) from GSE58486, GSE108940, and GSE115568 were screened and integrated via a robust rank aggregation algorithm. Then, the hub genes were identified and verified by the functional experiment of the MIRI mice. Finally, natural products with protective effects against MIRI were retrieved, and molecular docking simulations between hub genes and natural products were performed. Results. 230 integrated DEGs and 9 hub genes were identified. After verification, Emr1, Tyrobp, Itgb2, Fcgr2b, Cybb, and Fcer1g might be the most significant genes during MIRI. A total of 75 natural products were discovered. Most of them (especially araloside C, glycyrrhizic acid, ophiopogonin D, polyphyllin I, and punicalagin) showed good ability to bind the hub genes. Conclusions. Emr1, Tyrobp, Itgb2, Fcgr2b, Cybb, and Fcer1g might be critical in the pathological process of MIRI, and the natural products (araloside C, glycyrrhizic acid, ophiopogonin D, polyphyllin I, and punicalagin) targeting these hub genes exhibited potential therapeutic efficacy on MIRI. Our findings provided new insights to explore the mechanism and treatments for MIRI and revealed new therapeutic targets for natural products with protective properties against MIRI.
Parallel CNN Network Learning-Based Video Object Recognition for UAV Ground Detection
Authors: Liu Huanyu , Qiao Jiaqing , Li Lu , Wang Lei , Chu Hongyu , Wang Qingyu
Published: April 2022

Video object recognition for UAV ground detection is widely used in target search, daily patrol, environmental reconnaissance, and other fields. So, we propose the novel parallel deep learning network with the ability of the global and local joint feature extraction for the UAV video target detection. This paper focuses on solving the problems of feature extraction and target background discrimination required by target discovery to realize target discovery. Break through the key problems of real-time target recognition, such as multiscale targets, high background complexity, many small targets, dense target arrangement, and multidirection, and put forward an optimized network scheme, aiming at the problem of multiscale of image target and aiming at the problem of large change of target scale in image. In the network, the corresponding targets with different sizes and different aspect ratios are matched to make the different targets match the closest, and then, the position of the detection box is fine-tuned by regression. For the special problem of image viewing angle and for the rotation invariance of the airborne down looking image of the target, the usual solution is through data enhancement; that is, through the rotation transformation of the training data, the neural network can learn the rotation invariance of the target. Aiming at the problem of multi-directional image target and aiming at the problems of large target aspect ratio, large target tilt angle, and changeable direction in the target, we propose to use the tilt detection frame instead of the ordinary rectangular detection frame. Aiming at the problem of dense arrangement of image targets and aiming at a large number of densely arranged targets in the image, a feature refining module is proposed, which can effectively improve the detection performance of the detector for densely arranged targets. The experimental results shows that the proposed algorithm achieves more than 10% on the target detection accuracy with focal length change of 1-10 times. The detection accuracy meets the requirements of practical application.
Effect of Nigella Sativa Oil on Oxidative Stress, Inflammatory, and Glycemic Control Indices in Diabetic Hemodialysis Patients: A Randomized Double-Blind, Controlled Trial
Authors: Rahmani Alireza , Niknafs Bahram , Naseri Mohsen , Nouri Maryam , Tarighat-Esfanjani Ali
Published: April 2022

Background and Aims. Diabetes is a leading cause of renal failure. High levels of oxidative stress and inflammation in patients with renal diabetes lead to various disorders and mortality. This study was performed to determine the effect of Nigella sativa (NS) supplementation on superoxide dismutase (SOD), malondialdehyde (MDA), total antioxidant capacity (TAC), high-sensitivity C-reactive protein (hs-CRP), glycosylated hemoglobin (HbA1c), fasting blood sugar (FBS), and insulin (INS) in patients with diabetes mellitus undergoing hemodialysis (HD). Methods. In this randomized, double-blind, placebo-controlled clinical trial, a total of 46 diabetic HD patients were randomly divided into NS (n = 23) and placebo (n = 23) groups. NS group received 2 g/day of NS oil, and the placebo group received paraffin oil for 12 weeks. Serum levels of SOD, MDA, TAC, hs-CRP, HbA1C, FBS, and INS were measured before and after the study. Results. Compared to baseline values, SOD, TAC, and INS levels increased, whereas MDA, hs-CRP, HbA1c, and FBS significantly decreased. After adjusting for covariates using the ANCOVA test, changes in the concentrations of SOD (p = .040), MDA (p = .025), TAC (p=<.001), hs-CRP (p = .017), HbA1c (p = .014), and FBS (p = .027) were statistically significant compared to the placebo group. Intergroup changes in INS were not significant. Additionally, there were no notable side effects during the research. Conclusions. This study found that NS supplementation significantly enhanced the levels of SOD, MDA, TAC, hs-CRP, HbA1c, and FBS in diabetic HD patients.
A 3D Indoor Positioning Method of Wireless Network with Single Base Station in Multipath Environment
Authors: Wang Youqing , Zhao Kun , Zheng Zhengqi
Published: April 2022

The proliferation of indoor location-based services has increased the demand of indoor positioning technology. Severe multipath and coherence effects are the difference between signal propagation indoors and outdoors. Most existing indoor localization methods build their models in 2-dimensional space and try to avoid the influence of multipath. We propose a method to realize 3-dimensional indoor positioning with single base station by using multipath channel. The angles of multipath coherent signals are estimated by MIMO antenna and the delays are estimated by OFDM signal. To avoid the complicated calculation in joint estimation of angles and delays in 3-dimensional space, the angles and delays are estimated separately and matched by the proposed algorithm. The line-of-sight channel is differentiated by time delay, and the reflection paths for non-line-of-sight channels are established with angle information and indoor maps. Finally, combine the angle information of the reflection paths and the line-of-sight path to obtain the target position in 3-dimensional indoor space. We verified the method through simulation in an indoor space of

6
m
×
8
m
×
4.5
m

. The positioning errors are submeter level in

95
%

cases and less than 0.4m in

60
%

cases. The proposed method requires only one base station and can be applied in most wireless networks. Compared with existing indoor localization methods, it has lower computational complexity and higher application potential.
A Novel Dynamical Analysis Method for Platelet Aggregation: From Traffic Flow to Blood Flow
Authors: Qiu Min , Ren Jiahe , Xu Zhipeng
Published: April 2022

This study proposed an ordinary differential equation model to simulate platelet aggregation by considering the Stokes viscosity resistance and interaction force between each platelet. This model is similar to the car-following traffic model, and its stability condition can be derived via long-wave expansion. The phase diagram can be divided into stable, metastable, and unstable regions. The theoretical results show that the flow viscosity and platelet diameter play essential roles in thrombus formation. The mKdV equation near the critical point is derived to describe the platelet density waves’ evolution properties by applying the reductive perturbation method. Furthermore, through the simulation of the space-time evolution of the distance distributions for platelets, it is shown that a smaller platelet diameter and lower viscosity will lead to thrombus formation, and the analytical results are consistent with the simulation results. The model indicates that thrombosis is similar to traffic congestion.
Synthesis and Characterization of TiO2-Water Nanofluids
Authors: Surakasi Raviteja , Sripathi Srujana , Nadimpalli Sarada Purnima , Afzal Sibtain , Singh Bharat , Tripathi Manoj , Hafa Rahel Alemu
Published: April 2022

Nanofluids made of TiO2 and multiwalled carbon nanotubes are the focus of our study. Using TiO2 and water as the basic fluids, nanofluids were created in 100 : 0, 75 : 25, and 50 : 50 proportions. Carbon nanotubes (CNTs) were disseminated into these base fluids of three types at 0.125, 0.25, and 0.5 percentages. Over the course of two months, the change of zeta potential is monitored to assess the stability of the dispersion. XRD analysis and SEM and TEM analysis are carried out for TiO2 nanofluids. Nanoparticles were analyzed using EDAX analysis to identify their composition. SEM examination was used to investigate the morphology for TiO2 nanoparticles. Particles of TiO2 produced in this manner seemed to have an average diameter of 27 nm. Nanofluids have a poor stability, which is the most important aspect of employing them, although most studies did not focus on this. When it comes to nanofluids, this study is unique in that it provides an in-depth look of surface modification approaches that have been employed by researchers to address these issues, as well as an evaluation of their stability over two months. Solubility is improved by acid treatment of CNTs, which results in functional groups on the surface of CNTs.
Maintaining Diversity in Parallel Problem Solving: The Influence of Network Structure and Learning Strategy
Authors: Zhang Hua , Cao Chunhui
Published: April 2022

Recent research on maintaining diversity in parallel problem solving takes into consideration only network structure, without considering the agents’ learning strategies. In this paper, we use a simulation study to extend March’s classic model by using locomotion and assessment as agents’ problem‐solving strategies. First, we present a simulation framework that consists of external environment, communication networks, and agents’ learning strategies. Second, based on the framework, we develop March’s model to depict external environment. Third, we introduce four archetypical networks: a regular network, a small‐world network, a preferentially attached network, and a totally connected network as agents’ communication structure. Finally, we design three experiments to explore the performance implication of locomotors and assessors under different networks. Results suggest that network structure affects performance more than learning strategy. The more efficient the network is at diffusing knowledge, the better the performance in the short run but the worse in the long run. Locomotors can help keep diversity; a high proportion of locomotors’ team has a better final performance but need more equilibrium time. Furthermore, moderate composition among locomotors and assessors increases costly interaction uncertainty. We discuss the findings’ implications for the regulatory mode and problem‐solving literature.
Using Ensemble Learning Algorithms to Predict Student Failure and Enabling Customized Educational Paths
Authors: Smirani Lassaad K. , Yamani Hanaa A. , Menzli Leila Jamel , Boulahia Jihane A.
Published: April 2022

One of the challenges in e-learning is the customization of the learning environment to avoid learners’ failures. This paper proposes a Stacked Generalization for Failure Prediction (SGFP) model to improve students’ results. The SGFP model mixes three ensemble learning classifiers, namely, Light Gradient Boosting Machine (LGBM), eXtreme Gradient Boosting machine (XGB), and Random Forest (RF), using a Multilayer Perceptron (MLP). In fact, the model relies on high-quality training and testing datasets that are collected automatically from the analytic reports of the Blackboard Learning Management System (i.e., analytic for learn (A4L) and full grade center (FGC) modules. The SGFP algorithm was validated using heterogeneous data reflecting students’ interactivity degrees, educational performance, and skills. The main output of SGFP is a classification of students into three performance-based classes (class A: above average, class B: average, class C: below average). To avoid failures, the SGFP model uses the Blackboard Adaptive Release tool to design three learning paths where students have to follow automatically according to the class they belong to. The SGFP model was compared to base classifiers (LGBM, XGB, and RF). The results show that the mean and median accuracies of SGFP are higher. Moreover, it correctly identified students’ classifications with a sensitivity average of 97.3% and a precision average of 97.2%. Furthermore, SGFP had the highest F1-score of 97.1%. In addition, the used meta-classifier MLP has more accuracy than other Artificial Neural Network (ANN) algorithms, with an average of 97.3%. Once learned, tested, and validated, SGFP was applied to students before the end of the first semester of the 2020-2021 academic year at the College of Computer Sciences at Umm al-Qura University. The findings showed a significant increase in student success rates (98.86%). The drop rate declines from 12% to 1.14% for students in class C, for whom more customized assessment steps and materials are provided. SGFP outcomes may be beneficial for higher educational institutions within fully online or blended learning schemas to reduce the failure rate and improve the performance of program curriculum outcomes, especially in pandemic situations.
New Teaching Method of Body Training Course for Flight Attendants Based on Computer Multimedia Technology
Authors: Jia Chao
Published: April 2022

Physical training is a physical and mental training method with certain scientific basis and evaluation standards, and it is also one of the ways to cultivate comprehensive professionals for civil aviation. This paper attempts to incorporate multimedia computing systems into the teaching and learning of flight attendants from training classes, with the aim of tackling the issues that exist at this stage of the educational programme, promoting the standard and effectiveness of teaching and learning. Firstly, the paper explains the stewarding staff form training concept, including the professional requirements of flight attendants, the concept and characteristics of physical training, and the problems existing in the teaching process and then introduces the instruction system according to the multimedia computing system. Finally, this paper compares it using the classical teaching mode. The outcome of the investigation indicated that about 70% of the students achieved good grades and above with the assistance of multimedia computing devices, which verifies its effectiveness.
Asymptotic Prediction for Future Observations of a Random Sample of Unknown Continuous Distribution
Authors: El-Adll Magdy , Barakat H. M. , Aly Amany
Published: April 2022

When the first r lower extreme order statistics (failure times) of a sample of large size n,  1 < r < s < n, are observed, asymptotic predictive intervals of the future extreme order statistic with a rank s are constructed. The only assumption that we adopt is that the first failure time is attracted to the Weibull distribution. In addition, we suggest an efficient point estimator of its shape parameter and then a confidence interval is constructed for it. Moreover, new interesting asymptotic properties of the distributions that belong to the minimum domain of attraction of the Weibull distribution are revealed. Furthermore, extensive simulation studies are conducted to demonstrate the efficiency of the proposed methods. Two real datasets are analyzed to illustrate and corroborate the obtained results. The main results concern large samples.
A Quantitative Analysis of Country Relations in Foreign Direct Investment
Authors: Fu Huawei , Yan Li , Li Hua
Published: April 2022

According to Dunning’s eclectic theory, the location advantages play a key role in international investment mode choice, in which the country relations are important determinants. In some previous studies, the country relations and another bilateral factor, the country distance, are often confused, which can result in the inconsistency of conclusions. And excepting political factors, the economic dependence and other relations are insufficiently considered in the literature. This article makes a distinction between relation and distance, and puts forward a simplified analytical framework, the indicator system, and some quantitative methods for country relations. The indicators, including political, economic, and social factors, can better satisfy the horizontal analysis of the outbound investment. The economic and social indicators are determined by the magnitude of interaction as well as the share in the home country, and hence, the evaluation results can reflect the differences between the two countries. Finally, by evaluating the relations of other BRICS countries with China, the rationality is illustrated.
Fatigue Optimization of Structural Parameters for Orthotropic Steel Bridge Decks Using RSM and NSGA-II
Authors: Wang Zhiwen , Sun Shouwang , Ding Youliang
Published: April 2022

This study presents an optimization flow for structural parameters of orthotropic steel bridge decks (OSDs) based on the fatigue performance and the structural weight. The effects of structural parameters, namely, the thicknesses of the deck plate, the U-rib, the diaphragm, and the longitudinal diaphragm, on equivalent fatigue stress ranges were investigated using surrogate modelling based on the response surface methodology (RSM). Finally, the Pareto optimum front was obtained via the nondominated sorting genetic algorithm II (NSGA-II). The results show that the established surrogate response surface model can predict the local equivalent stress amplitudes well. The deck thickness is the most significant factor for the fatigue performance of the deck to U-rib weld and the U-rib to diaphragm weld. The objectives of minimizing the equivalent stress range and the total structural weight are truly conflicting, and the optimum solutions for structural parameters can be obtained from the Pareto optimum front.
Automating Group Management of Large-Scale IoT Botnets for Antitracking
Authors: Pan Pengyu , Ma Xiaobo , Fu Yingjie , Chen Feitong
Published: April 2022

With the popularity of Internet of Things (IoT) devices, IoT botnets like Mirai have been infecting as many devices as possible such as IP cameras and home routers. Because of the sheer volume and continual operation of many vulnerabilities (many users do not pay much attention to IoT update alerts and leave the configurations by default) of IoT devices, the population of an IoT botnet becomes increasingly tremendous. The growing population, though making a botnet powerful, results in an increased risk of exposure. Specifically, once a bot is captured, the command and control (C&C) channel may be cracked and then tracked, potentially rendering more bots being discovered. To solve this problem, this paper proposes an automated approach to group management of large-scale IoT bots. The basic idea of the proposed approach is to establish a reliable and unsuspicious social network-based C&C channel capable of automatically grouping bots, wherein a group of bots have a unique ID that is against cross-group tracking. The Diffie–Hellman key exchange method is leveraged for efficiently generating the unique group ID, thereby scaling up automatic bot grouping. We refer to the botnet proposed in this paper as a multichannel automatic grouping botnet (MCG botnet) and conduct verification experiments using social networks and more than 2,000 docker nodes. The experimental results show that the MCG botnet has the ability of automatic grouping and antitracking.
Digital Transformation of Listed Agricultural Companies in China: Practice, Performance, and Value Creation
Authors: Yang Ying , Cui Wenqin
Published: April 2022

In the digital economy era, the deep integration of the digital economy and the real economy promotes high-quality economic development. The digital transformation of listed agricultural companies in China, which is in a critical period of transformation and upgrading, is an important driving force for achieving high-quality agricultural development. This article takes Xinjinnong as an example to analyze how the practice of digital transformation can improve corporate performance and achieve value creation. The analysis found that in the initial stage of digital transformation (that is, the informationization stage, the company realized financial sharing, the person in charge of the company called the company digitalization 1.0 stage), this paper try to reduce costs and increase benefits by digital transformation from aspect of each link of production and operation (production link, operation link, supply chain management link, etc.) due to the low level of digitalization, the impact of digitalization on corporate performance is limited. The chain management link has achieved cost reduction and efficiency enhancement, and has significantly improved performance. The impact of digitalization on performance in production and application links is not obvious. With the deepening of digital transformation, Xinjinnong will realize value creation in the entire industry chain of the aquaculture industry in the digital 2.0 era.
Language Assessment Courses: An Investigation of the Course Instructors’ Pedagogical and Assessment Practices
Authors: Taghizadeh Masoomeh , Mazdayasna Golnar
Published: April 2022

Upon recognizing the significance of assessment literacy as a necessity for modern professional teachers, the quality of assessment courses has been examined from different angles. The present research aimed to examine the nature and functionality of assessment training at Iranian state universities in fostering the development of language assessment literacy (LAL), with a specific focus on the course instructors’ pedagogical practices (in terms of instructional materials/content and pedagogical practices) and assessment practices (including both formative and summative assessment). One hundred three course instructors were surveyed through a set of open-ended questions, and two course instructors’ pedagogical and assessment practices were observed throughout an educational semester. Based on the content and descriptive statistical analysis of the data, a lack of divergence in the instructors’ teaching and assessment practices was observable, with the majority of the instructors adhering to traditional methods, showing no inclination to adopt innovative practices. Lack of a balanced focus on all the core elements of LAL, being theory-laden and disconnected from practice in assessment, and use of dated teaching materials were recognized as factors or inappropriate practices on the part of the course instructors that might hinder the development of LAL in the researched context. Furthermore, a set of key action which might be taken by the course instructors to reduce the obstacles in developing and maintaining LAL has been suggested. Finally, limitations of the study and suggestions for future studies on LAL have been mentioned.
The Role of Zinc Finger Proteins in Various Oral Conditions
Authors: Agnihotri Rupali , Gaur Sumit
Published: April 2022

The zinc finger proteins (ZNFs) are essential transcription factors, and the genes encoding them constitute about 3% of the entire human genome. They are involved in the development of several tissues, and any alterations in their structure may promote chronic conditions like diabetes and tumorigenesis. Lately, their role in the development, progression, and metastasis of Oral Squamous Cell Carcinoma (OSCC), Epithelial Dysplasia, Oral Lichen Planus, and Periodontitis has been found. The present review aims to describe their role in various oral conditions. Electronic databases like Medline (PubMed) and Scopus were searched for original studies related to the role of ZNFs in various oral conditions. It yielded 48 studies included in the review. It was found that the ZNFs influenced chronic conditions like Oral Cancer and Periodontitis. They act both as tumor suppressors and oncogenes and have an anti-inflammatory effect. The knowledge from the present review may be utilized in designing drugs that prevent unusual expression of specific ZNFs. Besides, they may be applied as prognostic markers due to their high expression specificity in some tumors.
Extracts of Eucalyptus alba Promote Diabetic Wound Healing by Inhibiting α-Glucosidase and Stimulating Cell Proliferation
Authors: Mumtaz Rabia , Zubair Muhammad , Khan Muhammad Asaf , Muzammil Saima , Siddique Muhammad Hussnain
Published: April 2022

Treatment of diabetic wounds has always been a challenge for primary and acute health care. Eucalyptus alba has been reported to be used for the treatment of wounds and oxidative stress. Effects of using different temperatures and solvents for the extraction of Eucalyptus alba leaves were investigated in terms of diabetic wound healing activity. Leaves of E. alba were dried at 10°C, 30°C, 50°C, and 100°C, and dissolved in ethanol, methanol, and acetone to obtain a total of 12 extracts. All the extracts have remarkable antidiabetic, antioxidant, and cell proliferation activities. Among the tested extracts, highest activities were observed with leaves dried at 10°C and 30°C, whereas drying at 100°C resulted in the lowest activities. Ethanol-based extracts exhibited significantly increased cell proliferation compared with methanol- and acetone-based extract. The present study suggests that leaves of E. alba should be dried at temperature not more than 30°C and extracted in ethanol for optimum results. However, further studies should focus on the identification of specific bioactive compounds in E. alba leaves.
Medicinal Plants Used to Treat Human and Livestock Ailments in Basona Werana District, North Shewa Zone, Amhara Region, Ethiopia
Authors: Megersa Moa , Tamrat Nigussie
Published: April 2022

This study was conducted on medicinal plants used for the treatment of human and livestock ailments in Basona Werana District, North Shewa Zone, Amhara Region. Data were collected through semi-structured interviews, field walk observation, preference, and direct matrix ranking with randomly and purposefully selected informants. A total of 80 respondents (46 men and 14 women) and 20 (16 men and 4 women) traditional healers participated in this study. A total of 76 plant species distributed in 75 genera and 45 families were collected and identified. Of the 76 medicinal plants collected from the study area, 85.5% were used to treat human ailments. The Lamiaceae came out as a leading family with 8 (10.5%) species followed by Asteraceae and 7 (9%) medicinal plant species each, while Solanaceae followed with 6 (7.8%) species. The majority of medicinal plants were collected from wild habitat and accounted for 56 plant species (73.6%). The result of growth form analysis showed that herbs constituted the highest proportion of medicinal plants represented by 33 species (43.4%), followed by shrubs with 30 species (39.4%) and trees with 10 species (13.1%). The medicinal plants were administered through oral, which accounts for 54 species (48.1%), followed by dermal with 38 species (33.9%) and nasal with 9 species (8%), respectively. Leaves were the most frequently used plant parts for the preparation of traditional herbal medicines in the study area. Crushing was the widely used preparation method (33.9%) followed by pounding (16%). Cucumis ficifolius A. Rich. was the most preferred plant used to treat stomachache. Phytochemical and pharmacological studies of this type of plant are recommended to get the most out of the plant.
Improved Fuzzy Algorithm for College Students’ Academic Early Warning
Authors: Chen Siyu
Published: April 2022

The existing fuzzy clustering algorithms are mostly fuzzy comprehensive evaluation algorithms based on specific elements, but the main problem of such fuzzy algorithms is the lack of overall research on the responsible individuals and the lack of hierarchy in the algorithms. It is suitable for data mining of academic early warning systems. Therefore, an improved fuzzy algorithm based on fuzzy performance evaluation based on composite elements is proposed, and it is applied to the performance evaluation system to solve the complex problems in performance evaluation. In the process of building smart campuses in colleges and universities, academic prewarning, as the main part of smart campuses, mainly uses data mining technology to ensure students complete their studies smoothly and at the same time provides certain decision-making support for colleges and universities. Based on the research topic of the relevant departments of a certain school, this paper aims to build an academic early warning system suitable for the school to ensure that students can successfully complete their studies. The main research contents are divided into two parts: “study early warning model research” and “design and implementation of an academic early warning system.” Through analysis and experiments, it is proved that the model evaluation effect based on the algorithm improvement is the best, with recall reaching 85%, precision reaching 78.96%, and AUC reaching 80.25%.
A New Boosting Algorithm for Shrinkage Curve Learning
Authors: Meng Xiyan , Zhuang Fang
Published: April 2022

To a large extent, classical boosting denoising algorithms can improve denoising performance. However, these algorithms can only work well when the denoisers are linear. In this paper, we propose a boosting algorithm that can be used for a nonlinear denoiser. We further implement the proposed algorithm into a shrinkage curve learning denoising algorithm, which is a nonlinear denoiser. Concurrently, the convergence of the proposed algorithm is proved. Experimental results indicate that the proposed algorithm is effective and the dependence of the shrinkage curve learning denoising algorithm on training samples has improved. In addition, the proposed algorithm can achieve better performance in terms of visual quality and peak signal-to-noise ratio (PSNR).
Phase Transformation, Microstructures, and Mechanical Properties of α + β Two-Phase Titanium Alloy Deposited Metal by Surfacing Welding
Authors: Fang Naiwen , Huang Ruisheng , Xu Kai , Zhang Tianli , Wu Pengbo , Ma Yiming , Cao Hao , Qin Jian , Zou Jipeng
Published: April 2022

The effect of cooling rate on phase transformation, microstructures, and mechanical properties of TC4 titanium alloy deposited metal by laser surfacing welding with filler wire was investigated by in situ observation with a high-temperature laser confocal microscope, XRD, SEM, and through microhardness test. The results showed that primary α phase began to appear at grain boundaries when the deposited metal was heated to 890.5°C, and microstructures were all composed of coarse β columnar grains after the temperature was raised to 1 190.2°C; with the increase of cooling rate during the cooling process, temperature for starting new phase transformation decreased from 943.7°C to 811.1°C, and temperature for ending the transformation increased gradually from 708.0°C to 736.2°C; when cooled to room temperature at a rate of 1°C/s, microstructures consisted of α phase; at a rate of 15°C/s, acicular α′ martensite appeared in the microstructures; at 100°C/s, the microstructures were completely comprised by acicular α′ martensite; when the cooling rate was low, V element would be slightly precipitated from αgb into the matrix; when cooling turned faster, V element had no time to enter the matrix by diffusion, so it became uniformly distributed; as the cooling rate getting faster, lamellar microstructures became thinner gradually, and microhardness of the deposited metal was improved in a gradual manner.