bluuebunny/crossref_metadata_2025 huggingface dataset:
Endovascular treatment of acute tandem lesions in patients with mild anterior circulation stroke
Authors: Meyer Lukas , Politi Maria , Alexandrou Maria , Roth Christian , Kastrup Andreas , Mpotsaris Anastasios , Hanning Uta , Flottmann Fabian , Brekenfeld Caspar , Deb-Chatterji Milani , Thomalla Goetz , Kniep Helge , Faizy Tobias D , Bechstein Matthias , Broocks Gabriel , Herzberg Moriz , Feil Katharina , Kellert Lars , Dorn Franziska , Zeleňák Kamil , Fiehler Jens , Papanagiotou Panagiotis
Published: August 2022

Background

In patients with mild strokes the risk–benefit ratio of endovascular treatment (EVT) for tandem lesions has yet to be evaluated outside of current guideline recommendations. This study investigates the frequency as well as procedural and safety outcomes in daily clinical practice.

Methods

Using data from the German Stroke Registry-Endovascular Treatment (GSR-ET) we analyzed patients with anterior circulation stroke due to tandem-lesions and mild deficits. These patients were defined as ≤5 on the National Institutes of Health Stroke Scale (NIHSS). Recanalization was assessed with the modified Thrombolysis in Cerebral Infarction Scale (mTICI). Early neurological and long-term functional outcomes were assessed with the NIHSS change and modified Rankin scale (mRS), respectively. Safety assessment included periprocedural complications and the rate of symptomatic intracerebral hemorrhage (sICH).

Results

A total of 61 patients met the inclusion criteria and were treated endovascularly for tandem lesions. The median age was 68 (IQR:59–76) and 32.9% (20) were female. Patients were admitted to the hospital with a median NIHSS score of 4 (IQR:2–5) and a median Alberta Stroke Programme Early CT Score (ASPECTS) of 9 (IQR:8–10). Successful recanalization (mTICI 2b-3) was observed in 86.9% (53). NIHSS decreased non-significantly (p=0.382) from baseline to two points (IQR:1–9) at discharge. Excellent (mRS≤1) and favorable (mRS≤2) long-term functional outcome at 90-days was 55.8% (29) and 69.2% (36), respectively. Mortality rates at 90-days were 9.6% (5) and sICH occurred in 8.2% (5).

Conclusions

EVT for tandem lesions in patients with mild anterior circulation stroke appears to be feasible but may lead to increased rates of sICH. Further studies comparing endovascular with best medical treatment (BMT) especially investigating the risk of periprocedural hemorrhagic complications, are needed.
Physiological and radiological parameters predicting outcome from penetrating traumatic brain injury treated in the deployed military setting
Authors: Breeze John , Whitford A , Gensheimer W G , Berg C
Published: August 2022

Introduction

Penetrating traumatic brain injury (TBI) is the most common cause of death in current military conflicts, and results in significant morbidity in survivors. Identifying those physiological and radiological parameters associated with worse clinical outcomes following penetrating TBI in the austere setting may assist military clinicians to provide optimal care.

Method

All emergency neurosurgical procedures performed at a Role 3 Medical Treatment Facility in Afghanistan for penetrating TBI between 01 January 2016 and 18 December 2020 were analysed. The odds of certain clinical outcomes (death and functional dependence post-discharge) occurring following surgery were matched to existing agreed preoperative variables described in current US and UK military guidelines. Additional physiological and radiological variables including those comprising the Rotterdam criteria of TBI used in civilian settings were additionally analysed to determine their potential utility in a military austere setting.

Results

55 casualties with penetrating TBI underwent surgery, all either by decompressive craniectomy (n=42) or craniotomy±elevation of skull fragments (n=13). The odds of dying in hospital attributable to TBI were greater with casualties with increased glucose on arrival (OR=70.014, CI=3.0399 to 1612.528, OR=70.014, p=0.008) or a mean arterial pressure <90 mm Hg (OR=4.721, CI=0.969 to 22.979, p=0.049). Preoperative hyperglycaemia was also associated with increased odds of being functionally dependent on others on discharge (OR=11.165, CI=1.905 to 65.427, p=0.007). Bihemispheric injury had greater odds of being functionally dependent on others at discharge (OR=5.275, CI=1.094 to 25.433, p=0.038).

Conclusions

We would recommend that consideration of these three additional preoperative clinical parameters (hyperglycaemia, hypotension and bihemispheric injury on CT) when managing penetrating TBI be considered in future updates of guidelines for deployed neurosurgical care.
On the way to the 10 ps time-of-flight PET challenge
Authors: Lecoq P.
Published: August 2022

There is a consensus for gathering the multidisciplinary academic and industrial medical imaging community around the ambitious challenge to develop a 10 ps Time-of-Flight PET scanner (TOFPET). The goal is to reduce the radiation dose (currently 5–25 mSv for whole-body PET/CT) and/or scan time (currently > 10 min) by an order of magnitude, with a significant gain in the patient comfort and cost per exam (currently in the range of 1000 € per scan). To achieve this very ambitious goal it is essential to significantly improve the performance of each component of the detection chain: light production, light transport, photodetection, readout electronics. Speeding up progress in this direction is the goal of the challenge and will have an important impact on the development of a new generation of ionization radiation detectors. The possibility to reach 10 ps time-of-flight resolution at small energies (511 keV), as required in finely granulated calorimeters and PET scanners, although extremely challenging, is not limited by physical barriers and a number of disruptive technologies, such as multifunctional heterostructures, combining the high stopping power of well-known scintillators with the ultrafast photon emission resulting from the 1D, 2D or 3D quantum confinement of the excitons in nanocrystals, photonic crystals, photonic fibers, as well as new concepts of 3D digital SiPM structures, open the way to new radiation detector concepts with unprecedented performance.
Heat transfer analysis in the peristaltic flow of Casson nanofluid through asymmetric channel with velocity and thermal slips: Applications in a complex system
Authors: Irfan Muhammad , Nazeer Mubbashar , Hussain Farooq , Siddique Imran
Published: August 2022

This investigation articulately addresses the role of gold nanoparticles in medical sciences from a different perspective. Aiming to highlight the significant usage of nanoparticles, four different types such as spherical, platelets, cylindrical and brick-like nanoparticles are brought into consideration with the main focus to achieve maximum heat enhancement. This motivation leads to mathematically formulating an electroosmosis blood flow. Casson fluid is treated as physiological fluid through an asymmetric microchannel. The nonlinear term of radiative heat flux is added on the right-hand side of the heat equation to report the impact of radiation which is beneficial in skin diseases. A closed-form solution is achieved with the help of physical approximation. Moreover, analytical expressions for velocity distribution, temperature field, shear stress, heat transfer rate and pressure gradient have been provided. The expression of stream function is also presented and the trapping phenomena are discussed. Besides studying the tremendous capacity of gold particles to enhance the heat transfer rate for targeting the maligned tissues as a prime objective, the current survey will also assist readers to explore the other similar metallic particles which can effectively be used as an alternative.
Improving Just-In-Time Comment Updating via AST Edit Sequence
Authors: Huang Jiawen , Yu Huiqun , Fan Guisheng , Zhou Ziyi , Li Mingchen
Published: August 2022

Code comments are valuable for program comprehension and software maintenance. However, comments can be inconsistent or out-of-date after code changes. To tackle this problem, Just-In-Time (JIT) comment updating aims to automatically update comments with code changes. Existing approaches for this task use edit sequences of source code to model code changes. Meanwhile, recent researches indicate that neural models based on abstract syntax trees (AST) can help represent source code. In this paper, we propose a new method to learn code changes by combining code edit sequences with AST edit sequences, so that the generated new comment can be more accurate. Our approach utilizes three encoders to encode code edit sequences, AST edit sequences and old comment token sequences, respectively. The outputs of the encoders are then decoded into a sequence of edit actions, which is parsed to generate a new comment. The proposed method is evaluated on a public dataset using seven metrics, and the experimental results show that our approach outperforms the baselines. Furthermore, when the new comment has a larger edit distance than the old one, our model shows better performance.
Class Change Prediction by Incorporating Community Smell: An Empirical Study
Authors: Dou Qingyuan , Chen Junhua , Gao Jianhua , Huang Zijie
Published: August 2022

To adapt to changing software requirements, developers need to maintain and modify software through code changes. Predicting change-prone code can help developers to reduce the cost of software maintenance in advance. Prior work confirmed code smell intensity is a reliable metric for predicting change-prone classes. Community smell is a derivation of the concept of code smell in open-source software development community, it refers to poor communication and collaboration problems among developers. We add community smell to existing change prediction models, and propose a software class change prediction model integrating process metrics, code smell intensity metrics, anti-pattern metrics and community smell metrics, which takes into account the technicality and organizational aspects of software development. Experimental results demonstrate that when Multilayer Perceptron is used to build a change prediction model, community smell improves the baseline model by 4.4% and 31.5% in terms of [Formula: see text]-Measure and Recall. In addition, community smell improves baseline model performance to a greater extent in terms of Recall and Precision than code smell-related information.
Parametrically Excited Instability of Periodic Visco-Elastomer Sandwich Plate with Supported Masses Under Quadrilateral Longitudinal Harmonic Excitations
Authors: Ying Z. G. , Ruan Z. G. , Ni Y. Q.
Published: August 2022

The parametrically excited instability of the spatially periodic visco-elastomer sandwich plate with supported masses under quadrilateral longitudinal temporal harmonic excitations is studied. The improvability of the parametrically excited instability by periodic distribution parameters is explored. The direct eigenvalue analysis approach for solving the parametrically excited stability problem of the periodic sandwich plate system under longitudinal harmonic excitations is proposed. The spatial periodic distribution of facial layer thickness and core layer modulus of the sandwich plate is considered. The non-linear partial differential equations of longitudinal and transverse coupling motions of the periodic visco-elastomer sandwich plate with supported masses under biaxial longitudinal boundary excitations are derived. The longitudinal displacements of the sandwich plate are separated into two parts and the longitudinal boundary excitations relevant to symmetric part are incorporated into the sandwich plate system. Then the partial differential equations with boundary excitations are converted into parametrically excited system equations and further converted into ordinary differential equations with time-varying parameters, which describe the parametrically excited vibration with multi-mode coupling of the periodic sandwich plate system. The fundamental perturbation solution to the equations is expressed as the product of periodic and exponential parts based on the Floquet theorem. The ordinary differential equations with harmonic parameters are converted into a set of algebraic equations using the harmonic balance method. Then the parametrically excited instability of the periodic sandwich plate system is determined directly by matrix eigenvalues. The overall instability characteristics of parametrically excited vibration with multi-mode coupling of the system under longitudinal harmonic excitations are illustrated by numerical results on unstable regions. The parametrically excited instability can be improved by the spatially periodic distribution of geometrical and physical parameters. The proposed approach is applicable to general sandwich structures with spatial distribution parameters in multi-mode-coupling parametrically excited vibrations for overall instability analysis on continuous frequency band.
DEEP LEARNING APPROACHES FOR ANOMALIES DETECTION OF BLADDER CT CONTOURS IN PROSTATE CANCER PATIENTS
Authors: SU CHONG , TU TAO , HAN PEIJIN , LAKSHMINARAYANAN PRANAV , McNUTT TODD
Published: August 2022

In radiation therapy, poor contour delineations of Region of Interests (ROI) may result in incorrect radiation dosing and increase the chance of radiation-induced toxicities. To better recognize these contours, we used a feature fusion-based 3-dimensional convolution neural network (3D-CNN), multi-view convolution neural network (MV-CNN), and 3D point cloud to retrospectively detect abnormal bladder contours among prostate cancer patients. We defined three patterns of abnormal bladder contours: (1) discontinuities: missing slices and disparate volumes, (2) surface aberrations: extended or contracted slices, (3) small volume: bladder volume [Formula: see text][Formula: see text]ml. We created virtual samples for discontinuities and surface aberrations by randomly adding pixel to one or more slices outside the original contours and randomly extending or shrinking one or more slices. For both 3D-CNN and MV-CNN methods, we utilized the Local Binary Pattern (LBP) and Canny operators for feature extraction and compared several feature fusion-based approaches, including Original image + LBP processed image, Original image + Canny processed image, Original image + LBP processed image + Canny processed image. For the 3D point cloud, we applied the 3D point cloud segmentation method (Rand LA-Net) and the 3D point cloud classifying method (DGCNN). We had 344 samples available (219 real contours and 125 virtual contours) altogether. All the algorithms were trained on 200 bladder contours, validated on 100 bladders, then tested on 44 real annotated contours. Among all the approaches, the “Original + LBP”-based MV-CNN model achieved the highest accuracy: 100% for predicting discontinuity and small volume, 91.3% for predicting normal contours, and 90.9% for predicting surface aberrations. MV-CNN performed more accurately and efficiently across all the feature fusion methods. In particular, “Original + LBP”-based MV-CNN achieved the highest test accuracy. Our tools can detect anomalies of bladder contours in clinical settings and may improve the process of contour quality assurance (QA).
ANTHROPOMETRY, MOTION RANGE, AND MUSCLE STRENGTH MEASUREMENTS OF AMPUTEES FOR DESIGNING LARGE-SCALE AGRICULTURAL EQUIPMENT
Authors: SON BYUNG CHANG , PARK YEONGJEONG , CHOI JUNG KAB , YOO SO YOUNG , PARK SEJIN , KIM HYUN JOONG , KIM HA YOUNG , YOOK JUHYE
Published: August 2022

The purpose of this study is to derive and analyze the static, dynamic, and muscle strength measurement items of amputees in Korea for the design of large-scale agricultural work equipment considering their altered physical characteristics and functions. A total of 46 amputees participated in the study, with 34 males and 12 females in the age ranging between 30 and 60 years. Thirty items were derived for the measurement items considering the designing of the large-scale agricultural work equipment. The measurement results were presented as 5%tiles, 50%tiles, and 95%tiles values by item and gender, and t-test verification was performed on gender basis. There was a statistically significant difference between the men and women in most of the measurement items. Our results indicate that the male data should be used for the spatial design of equipment with static measurement items and the design of the controllers with dynamic measurement items, whereas the female data should be applied in the designing of parts that require muscle strength, such as accelerators. The results of this study can provide a basic data for developing the design of large-scale agricultural work equipment and machines that are usable and convenient for amputees in Korea, and in exploring the anthropometric measurements of the subtypes of people with physical disabilities.
Superconvergence of an Ultra-Weak Discontinuous Galerkin Method for Nonlinear Second-Order Initial-Value Problems
Authors: Baccouch Mahboub
Published: August 2022

In this paper, we develop and analyze an ultra-weak discontinuous Galerkin (UWDG) method for nonlinear second-order initial-value problems for ordinary differential equations of the form [Formula: see text]. Our main concern is to study the convergence and superconvergence properties of the proposed scheme. With a suitable choice of the numerical fluxes, we prove the optimal error estimates with order [Formula: see text] in the [Formula: see text]-norm for the solution, when piecewise polynomials of degree at most [Formula: see text] are used. We use these results to prove that the UWDG solution is superconvergent with order [Formula: see text] for [Formula: see text] and [Formula: see text] for [Formula: see text] towards a special projection of the exact solution. We further prove that the [Formula: see text]-degree UWDG solution and its derivative are [Formula: see text] superconvergent at the end of each step. Our proofs are valid for arbitrary regular meshes using piecewise polynomials with degree [Formula: see text]. Finally, numerical experiments are provided to verify that all theoretical findings are sharp. The main advantage of our method over the standard DG method for systems of first-order equations is that the UWDG method can be applied without introducing any auxiliary variables or rewriting the original equation into a larger system, which reduces memory and computational costs.
Constructing Japanese Bullying Expression Dictionary for Automated Cyberbullying Detection on Twitter
Authors: Zhang Jianwei , Li Lin , Nakajima Shinsuke
Published: August 2022

Cyberbullying has become a serious problem with the spread of personal computers, smartphones and SNS. In this paper, for automated cyberbullying detection on Twitter, we construct a Japanese bullying expression dictionary, which registers bullying words and their degrees related to bullying. The words registered in the dictionary are those that appear in the collected bullying-related tweets, and the bullying degrees attached to the words are calculated using Semantic Orientation Using Pointwise Mutual Information (SO-PMI). We also construct models to automatically classify bullying and non-bullying tweets by extracting multiple features including those drawn from the bullying expression dictionary and combining them with multiple machine learning algorithms. We evaluate the classification performance of bullying and non-bullying tweets using the constructed models. The experimental results show that the bullying expression dictionary can contribute to cyberbullying detection in most of the machine learning algorithms and that the best model can achieve an [Formula: see text]-measure value exceeding 0.9. We further investigate whether the periods of constructing bullying expression dictionaries affect the classification performance. The experimental results indicate that in contrast to the period of dictionary construction, the number of registered words has more immediate impact on classification performance.
Modeling of Mg12O11–X (X = B, N, P and S) Nanostructured Materials as Sensors for Melamine (C3H6N6)
Authors: Louis Hitler , Udoh Esther U. , Amodu Ismail O. , Ekereke Ernest E. , Isang Bartholomew B. , Onyebuenyi Izubundu B. , Adeyinka Adedapo S.
Published: August 2022

This research is focused on the sensor properties of pure and X-decorated ([Formula: see text], N, P and S) magnesium oxide (Mg[Formula: see text]O[Formula: see text]) nanocages for melamine (C3H6N6) molecule detection using density functional theory (DFT) electronic structure approach. Comparative adsorption study was carried out on four distinct computational models of hybrid functionals: [Formula: see text]B97XD, PBE0-D3BJ, M062X-D3BJ and DSDPBEP86 with the double-hybrid (DSDPBEP86), being the superior model at the fifth rung of the Jacobi’s ladder, was used as the reference. The atoms-in-molecule (AIM), alongside with the non-covalent interactions (NCIs) as visual extension had been utilized in the study of weak interactions and to affirm the degree of interactions between the clusters and the toxin. In all cases, this study suggests that the adsorption phenomena are best described as chemisorption due to the negative adsorption enthalpy observed. The mean absolute deviation (MAD) and root mean square deviation (RMSD) statistical approaches suggest the behavior of the possible adsorptions to be ranked as follows: PBE0-D3BJ (first rank), [Formula: see text]B97XD (second rank) and finally, M062X-D3BJ (third rank) with ([Formula: see text], 0.7870 and 0.8402) and ([Formula: see text], 0.8946 and 0.9560), respectively. These results are consistent with those of the topological and the sensing parameters, hence, arriving at a conclusive scientific report that Mg[Formula: see text]O[Formula: see text] and Mg[Formula: see text]PO[Formula: see text] surfaces exhibit relatively better sensing performances for the trapping of melamine (MB).
A Summary Indicator Providing a Snapshot of Political Opinions when Variables are Ordinal
Authors: Deutsch Joseph , Silber Jacques
Published: August 2022

This paper deals with the evaluation of the relative performance of different groups when the achievements of the members of a group are summarised by the relative distribution of these achievements across various ordered categories. After reviewing a previous attempt by Herrero and Vilar to deal with this issue, we propose to adopt an approach introduced recently by Apouey, Silber and Xu who derived a measure of achievement that, in the case of ordinal variables, takes account of both the inequality and the location of a distribution. Their approach is then applied to the analysis of political opinions, using the International Social Survey Programme for the year 2009. We compare questions dealing with respectively the need for the government to reduce income inequality, the duty of the government to help poor and unemployed individuals and the inequality of opportunity in health and education. It appears that the correlations obtained for our summary indicator of political opinions, based on the data covering 41 countries, reflect quite well the distinction we made between the three types of questions on political opinions. In addition, regression results show that generally the higher the inequality in a country, the more likely it is that people will approve government intervention aimed at reducing inequality and poverty.
VizWiz grand challenge workshop at CVPR 2022
Authors: Massiceti Daniela , Anjum Samreen , Gurari Danna
Published: August 2022

Our goal is to educate a broader population about the technological needs and interests of people with vision impairments while encouraging artificial intelligence (AI) researchers to develop new algorithms that can help eliminate accessibility barriers. Towards this goal, we organised the VizWiz Grand Challenge Workshop at the IEEE/CVF Computer Vision and Pattern Recognition conference (CVPR 2022). This workshop's scope included charting and celebrating progress on accessibility-related AI challenges as well as engaging invited speakers and stakeholders to discuss challenges and opportunities related to designing next-generation assistive technologies. A total of 72 teams participated in our three AI challenges and the winners received awards sponsored by Microsoft. The facilitated discussions highlighted insights from ten invited speakers who provided a range of expertise spanning the cutting edge of computer vision research, development of industry products and services for assisting people with vision impairments, and perspectives of people with vision impairments who use visual assistance technologies. Finally, nine teams who submitted extended abstracts about their research related to the AI challenges and assistive technologies for people with visual impairments gave spotlight and poster presentations about their research. Links to the content shared at the event can be found at VizWiz Workshop
Point-of-Care DNA Amplification for Disease Diagnosis and Management
Authors: Botella José R.
Published: August 2022

Early detection of pests and pathogens is of paramount importance in reducing agricultural losses. One approach to early detection is point-of-care (POC) diagnostics, which can provide early warning and therefore allow fast deployment of preventive measures to slow down the establishment of crop diseases. Among the available diagnostic technologies, nucleic acid amplification–based diagnostics provide the highest sensitivity and specificity, and those technologies that forego the requirement for thermocycling show the most potential for use at POC. In this review, I discuss the progress, advantages, and disadvantages of the established and most promising POC amplification technologies. The success and usefulness of POC amplification are ultimately dependent on the availability of POC-friendly nucleic acid extraction methods and amplification readouts, which are also briefly discussed in the review.
Energy-Saving Electrochemical Hydrogen Production on Dynamic Hydrogen Bubble-Template Electrodeposited Ni-Cu-Mn Nano-Micro Dendrite
Authors: Lotfi N. , Barati Darband Gh.
Published: August 2022

Replacing an oxidation reaction with lower potential than OER can significantly reduce the cell potential in the hydrogen production process. Here, we synthesized Ni-Cu-Mn alloy nano-micro dendrites using one-step and binder-free dynamic hydrogen bubble template (DHBT) electrochemical deposition method and studied its activity for urea oxidation reaction (UOR) and hydrogen evolution reaction (HER). Electrochemical results for HER represented that the η
10 for the optimized electrode is 63 mV and its Tafel slope is 111 mV.dec−1. Also, the results of polarization tests showed that by replacing the OER process with UOR, in the overall water splitting process, to create a current density of 10 mA.cm−2 the cell potential reaches 1.361 V, which is 179 mV less than HER-OER. Also, the results of electrocatalytic stability represented small changes in overpotential during the electrolysis process, which indicates the unique electrocatalytic stability. The improvement of electrocatalytic results in this study is due to the fabrication of a binder-free and three-dimensional surface as well as the synergistic effect caused by elements in improving the intrinsic electrocatalytic activity. This study revealed that the use of DHBT method can be used effectively to synthesizing active and cost-effective bi-functional electrocatalysts for HER-UOR.
An experiential learning course for cardiovascular and sleep technology
Authors: Durocher John J. , Toorongian Colleen A. , Thivierge Grant S.
Published: August 2022

Experiential learning in clinical exercise, autonomic regulation, and sleep physiology is an impactful way to train undergraduate biomedical students to enter a variety of careers in healthcare, graduate programs in the health professions, or traditional research graduate programs. A hands-on course such as Cardiovascular and Sleep Technology provides a way, in addition to or independent of original research, to provide clinically relevant training.
Cardiac micro-RNA and transcriptomic profile of a novel swine model of chronic kidney disease and left ventricular diastolic dysfunction
Authors: Chade Alejandro R. , Eirin Alfonso
Published: August 2022

Chronic kidney disease (CKD) is a progressive disorder in which more than 50% of deaths are attributed to cardiovascular disease. Using a swine model of CKD that develops left ventricular dysfunction (CKD-LVDD), we characterize the cardiac micro-RNA and transcriptomic profile, identifying dysregulated genes associated with cardiac remodeling and fatty acid metabolism that might be post-transcriptionally regulated early in the disease. These findings pinpointed pathological pathways that may open new avenues toward therapeutic research to reduce cardiovascular morbidity in CKD.
Role of coagulation in persistent renal ischemia following reperfusion in an animal model
Authors: Dominguez Jesus H. , Xie Danhui , Dominguez James M. , Kelly K. J.
Published: August 2022

Ischemic renal injury carries very high morbidity and mortality, yet has no specific therapy. We found markedly decreased, heterogeneous microvascular plasma flow, tissue factor induction, fibrin deposition, and microthrombi after renal ischemia-reperfusion using a well-characterized model. Renal exosomes or the fibrinolytic urokinase, administered after renal failure was established, improved microvascular flow, coagulation, renal function, and histology. Data demonstrate that intrarenal clotting results in sustained ischemia amenable to therapy that improves both function and postischemic inflammation.
Fatigue Performance of Steel Slag SMC Ultrathin Abrasive Layer Under Strain Controlling Mode
Authors: He Shuyun , Gao Lingling , Guo Chaoyang , Wu Xianhu
Published: August 2022

Recently, the warm mixing modified ultrathin abrasive layer has been paid great attention due to the green energy-saving strength. In regard to its durability, the study of the fatigue behavior of the SMC warm mixing modified ultrathin abrasive layer asphalt mixture was carried out under the strain controlling mode. The relationship among all characteristic parameters (bending stiffness modulus, normalized times, and products phase angle) and stress cycle times showed a similar three-stage change process, except for the accumulative dissipated energy. The transition point (Nf) between the second (RDEC2) and the third stage (RDEC3) was assumed to be the characteristic fatigue cracking sign for the SMC warm mixing modified ultrathin abrasive layer. In that case, supported by multiobjective system, the relative change of dissipation energy, rather than the 50% initial stiffness, was regarded as the appropriate fatigue cracking criteria.
Meal Pattern in the Colombian Population: Results of the National Nutrition Survey. ENSIN, 2015
Authors: Zea María del Pilar , Herrán Oscar F.
Published: August 2022

Background. Information on meal patterns (type, number, relative contribution to energy/day (%), time, and location of meals) is limited or nonexistent. Design. Cross-sectional, nationally representative surveys. Setting. Colombia. Participants. n = 26,115 from 3 to 64 years old. The sample analyzed included 3,127 children between 3 and 4 years old, 13,384 children between 5 and 17 years old, and 9,604 adults between 18 and 64 years old. Data Analysis. Meal patterns were described by age group. Through multiple linear regression, crude and adjusted differences in the categories of the covariates studied were estimated. The number/day of meals was the dependent variable. Results. The number of meals/day (mean ± SD) was 4.4 ± 0.0, without differences by sex

P
=
0.068

, current weight

P
=
0.336

, or wealth index

P
=
0.480

, but there were differences in the level of education of the head of the household

P
<
0.0001

and the level of food security of the household

P
<
0.0001

. A total of 96.8% of the population eats 3 or more meals/day (95% CI: 96.2, 97.2). The consumption frequency (mean ± SD) of the three main meals was 0.95 ± 0.0 “times/day,” 1.0 ± 0.0 and 0.95 ± 0.0, for breakfast, lunch, and dinner, respectively. Lunch is the meal that makes the greatest relative contribution to the total energy consumed (energy/day), 33.9% (95% CI: 32.7, 35.1). Breakfast is eaten outside the home by 13.0% of the subjects, lunch by 26.0%, and dinner by 3.8%. The minimum fasting interval is 9 hours and the maximum is 10 hours and 30 minutes. The meal pattern is equivalent to type “A,” with three main meals and two or three intermediate meals (midmorning and midafternoon) taken during 15 hours of the day. Conclusions. All age groups had more than four meals/day. The number is directly related to socioeconomic level. Lunch is the main meal.
Application Analysis of Overlapping Community Detection Algorithms for Multidimensional Network Big Data and IoT
Authors: Yang Xin , Cui Liping , Liu Yan
Published: August 2022

Capture the design and elements of these layers. Each layer corresponds to an alternative connection type between hubs in the normal world and requires tracking down communities in multidimensional networks. Most community disclosure approaches for multidimensional networks, then again, may ignore the transaction between layers or a layer’s unmistakable topological construction. Moreover, most of them are just equipped for distinguishing nonoverlapping communities. In this exploration, we offer another multidimensional network community disclosure strategy that exploits the connection among layers and the extraordinary geography of each layer to track down overlapping communities. First, use an overall assessment of edge behavior within and between layers to calculate the similarity of edges from similar layers and cross layers. You can then use these similarities to build a dendrogram of a multidimensional network that takes into account both characteristic topology structures and basic transactions. Finally, you can remove the overlapping communities in these layers by splitting the dendrogram and adding another community thickness metric for the multidimensional network. We show that our strategy is precise in recognizing overlapping communities in multidimensional networks by applying it to both manufactured and genuine world datasets. In chart and enormous information examination, community detection is a commonplace issue. It involves finding groups of firmly associated hubs with little associations with hubs outside the bunch. Distinguishing communities in huge scope networks, specifically, is a basic errand in numerous logical fields. In the writing, community detection techniques have been demonstrated to be wasteful, bringing about the improvement of communities with uproarious communications. To defeat this requirement, a framework that decides the best community among multifaceted networks in light of important determination standards and substance dimensionality should be created, eliminating loud communications in a continuous setting. Our outcomes likewise show that it is vital to utilize integral measurements to assess the exhibition of overlapping community detection calculations. Performance metrics, such as the NMI or the Omega Index, only measure the overall quality of a detected cover, whereas complementary metrics give us more information about the behavior of each algorithm in detecting overlapping communities. Finally, while some algorithms perform well on synthetic networks, none of the algorithms can detect the community structure in real networks. This is due to the detected communities of the algorithms being substantially different from the communities defined by the meta-data.
[Retracted] Downregulation of miR‐221‐3p by LncRNA TUG1 Promoting the Healing of Closed Tibial Fractures in Mice
Authors: Liu Laiyou , Yuan Yinpeng
Published: August 2022

Objective. To probe into the effect of LncRNA TUG1 on the healing of closed tibial fracture in mice. Methods. The closed tibial fracture model of mice was established, selecting the mouse osteoblast line MC3T3‐E1, with the cells separated into four groups. The expression levels of TUG1 and miR‐221‐3p were determined by RT‐qPCR analysis, with the targeting relationship between TUG1 and miR‐221‐3p authenticated by dual luciferase reporter (DLR) assay, detection of cell migration (CM) ability based on Transwell cell migration (TCM) assay, and cell proliferation (CP) acquired by cell counting kit‐8 (CCK‐8). Results. Prediction results of the target gene by bioinformatics software showed that miR‐221‐3p had binding sites with the 3′‐UTR of TUG1, and DLR assay authenticated the targeting relationship between LncRNA TUG1 and miR‐221‐3p. Downregulation of TUG1 inhibited osteoblast CP and CM and promoted osteoblast cell apoptosis (CA). Cell cycle analysis indicated that miR‐221‐3p provoked cell cycle arrest in G1 stage of MC3T3‐E1 cells. The siLncRNA‐NC group had higher anticyclin D1 and D3 levels than the siLncRNA TUG1 group, with a lower CA rate in the former, implying that miR‐221‐3p overexpression inhibited osteoblast CP and CM and LncRNA TUG1 inhibited CA. Downregulation of miR‐221‐3p partly reversed the retardation out of downregulating TUG1 on osteoblast CP and CM. Bcl‐2 level was higher in the LncRNA TUG1 group compared to the siLncRNA TUG1 and miR‐221‐3p overexpression groups, with remarkably lower SDF‐1 level in the miR‐221‐3p overexpression group than those in the control, miRNA‐NC, and LncRNA TUG1 groups. Conclusion. The downregulation of miR‐221‐3p by LncRNA TUG1 can promote the healing of closed tibial fractures in mice.
[Retracted] The Influence of Teachers’ Management Efficiency and Motivation on College Students’ Academic Achievement under Sustainable Innovation and the Cognition of Social Responsibility after Employment
Authors: Tan Chang , Yi Lianyun , Haider Aziz , Kwen Liew , Mamnoon Rahman , Li Keqing , Liu Min
Published: August 2022

Teachers’ management effectiveness can reflect the comprehensive ability and effective evaluation of the teaching management objectives of the school and can also reflect the effectiveness management of the school to a certain extent. In the environment of sustainable and innovative development, the rapid development of education has made improving the management efficiency and motivation of university teachers became the key direction of university management. In order to study the impact of teachers’ management efficacy and motivation on college students’ academic achievement and postemployment social responsibility cognition under sustainable innovation, this study compares the impact of teachers in different periods on students and analyzes the changes of teachers in different periods on students. Finally, it is concluded that teachers’ management efficiency and motivation under sustainable innovation can promote students’ employment achievement and social responsibility cognition, improve the teaching quality of colleges and universities, and provide high‐quality talents for the country. The educational concept of sustainable innovation is conducive to improving teachers’ independent innovation and realizing the educational function of cultivating students’ personalized development in colleges and universities.
Mathematical Modeling Method of the Improved Genetic Algorithm for Random Power Fluctuation
Authors: Zhu Fu
Published: August 2022

In order to solve the problem that the traditional genetic algorithm has a slow search speed and is easy to fall into the local optimal solution, a mathematical modeling method of an improved genetic algorithm in random power fluctuation is proposed. Drawing on the idea of a genetic algorithm (GA) and using the randomness and stability trend of cloud droplets of the normal cloud model, the author proposes a new genetic algorithm, cloud genetic algorithm (CGA). CGA is implemented by the Y-condition cloud generator of the normal cloud model to realize the cross operation, and the basic cloud generator realizes the mutation operation. Finally, the power function optimization experiment and the IIR digital filter optimization design are carried out, and the standard GA, NQGA, CAGA, and LARES algorithms are carried out compared. The experimental results show that the IIR digital filter designed by CGA has the smallest maximum ripple (Ap) in the passband, which is 0.342, and the largest minimum attenuation (As) in the stopband, which is 34.27. It can be observed that the overall performance is better. The validity of the algorithm is proved, and it has a certain reference and application value.
Disease Biomarkers of Giardiasis
Authors: Roshidi Norhamizah , Arifin Norsyahida
Published: August 2022

Giardiasis is a common, treatable intestinal disease that adversely affects underprivileged communities living in unsanitary conditions. Giardiasis causes a wide spectrum of gastrointestinal diseases in those infected, ranging from subclinical disease that can manifest as irritable bowel syndrome with persistent abdominal symptoms. Importantly, giardiasis has been identified as a predictor of malnutrition among young children in rural areas and as a cause of waterborne mass epidemics endangering not only humans but also animals in a broad clinical, social, and economic spectrum. While the diagnosis of giardiasis is heavily dependent on the presence of cysts and/or trophozoites detected using microscopy, the intermittent cyst excretion, low infection intensity, and low sensitivity method m4akes fecal examination unrewarding, thus urging the need for an improved diagnostic method for giardiasis. Proteins are key compounds in biosynthesis, cells, tissues, and organ signaling, carrying important information related to biological and pathogenic processes, as well as pharmacological responses to therapeutic intervention, and are therefore important indicators for determining disease onset, progression, and drug treatment effectiveness. In connection with this, proteins could serve as promising biomarkers for antigen-antibody detection, as well as vaccine candidates. This article is aimed at providing a comprehensive overview of proteins, serological, molecular, inflammatory, volatile, and hormonal biomarkers associated with giardiasis and their potential for diagnostics and therapeutics.
Deep-Learning-Guided Student Intelligent Classroom Management System
Authors: Niu Xiaobing
Published: August 2022

Aiming at the limitations of old-fashioned instructing knowledge and the insufficiency of existing dynamically managed classrooms, a deep-learning-guided Unity3D-based intelligent classroom management system and the corresponding instrument support were proposed. We first build a virtual scene and import Unity3D motors, in order to improve practical fake action proofs through C# script and prefix system. Subsequently, we attempt to solve the permission arrangement proposition in multiperson entity scenes, and accordingly, we complete the cognitive assistance module using authorization strategy. Our system can provide different students with tailored permissions, foresee text, video, and some flexible functions. Our system can be divided into multiple Spring Cloud frameworks. We further leverage the Redis to optimize the system architecture. The system can be conveniently applied in chemistry instructing with clear virtual auditions under the government direct supervision. It can effectively address authority issues in real scenarios while enhancing the learning efficiency and increasing accessibility. A set of intelligent classroom behavior system based on deep learning that supported by cunning learning methods are proposed accordingly. It can complete the classroom perception ministry. It can optimally conduct status monitoring as well as classroom assignment and discussion services through deep learning vision techniques such as face perception and facial expression analysis. Extensive experimental results have shown the competitive performance of our method.
Image Recognition of Pediatric Pneumonia Based on Fusion of Texture Features and Depth Features
Authors: Wang Hao-Nan , Zheng Li-Xin , Pan Shu-Wan , Yan Tan , Su Qiu-Ling
Published: August 2022

Pneumonia is one of the diseases that seriously endangers human health, and it is also the leading cause of death of children under the age of five in China. The most commonly used imaging examination method for radiologists is mainly based on chest X-ray images. Still, imaging errors often result during imaging examinations due to objective factors such as visual fatigue and lack of experience. Therefore, this paper proposes a feature fusion model, FC-VGG, based on the fusion of texture features (local binary pattern LBP and directional gradient histogram HOG) and depth features. The model improves model performance by adding detailed information in texture features to the convolutional neural network while making the model more suitable for clinical use. We input the X-ray image with texture features into the modified VGG16 model, C-VGG, and then add the Add fusion method to C-VGG for feature fusion so that FC-VGG is obtained, so FC-VGG has texture features detailed information and abstract information of deep features. Through experiments, our model has achieved 92.19% accuracy in recognizing children’s pneumonia images, 93.44% average precision, 92.19% average recall, and 92.81% average F1 coefficient, and the model performance exceeds existing deep learning models and traditional feature recognition algorithms.
Flutter Boundary Prediction Based on Structural Frequency Response Functions Acquired from Ground Test
Authors: Yu Changkun , Wu Zhigang , Yang Chao
Published: August 2022

Establishing an accurate, fast, and low-risk flutter boundary prediction method is of great significance for flight vehicle design. In this paper, a ground flutter boundary prediction method (GFBP) based on experimental structural frequency response functions (FRFs) is proposed. A low-order multi-input multi-output (MIMO) aeroelastic system is established by combining the structural FRFs acquired from a ground test and the calculated unsteady aerodynamic FRFs in physical coordinates. The multivariable Nyquist criterion is used to predict the flutter boundary. A fixed-root aluminum plate wing is selected as the research model. A GFBP experiment is carried out for the wing’s normal state, leading-edge clump weight state, and trailing-edge clump weight state. The feasibility and accuracy of the proposed method are verified by comparison with theoretical flutter results, in which the errors of flutter speed and frequency in the test statistics are no more than 1.7%. In a simulation model established by the proposed method, Monte Carlo simulation is used to study the influence of deviations in the mode frequency and damping of the structural FRFs and deviations in the positions of excitation and measurement points in the ground test. The experiment and simulation results show that the proposed method can predict the flutter boundary accurately with accurate positions of excitation and measurement points, and it has good robustness to deviations in the mode frequency and amplitude of the structural FRFs.
[Retracted] The Value of CBL‐Based Teaching Mode in Training Medical Students’ Achievement Rate, Practical Ability, and Psychological Quality
Authors: Zhao Yaying , Liu Wenfang , Wang Zhemin , Chen Xinglin , Zhao Jinying , Zhou Xianbo
Published: August 2022

In order to improve the quality of medical student training, the clinical case‐based learning (CBL) teaching mode is analyzed in the aspect of the rate of achievement, practical ability, and psychological effect. A total of 86 medical students who came to our hospital from March 2020 to December 2021 are selected and divided into the CBL group and the control group according to the random number table method. The psychological quality of medical students is evaluated by observing their movements and expressions during their internship. In addition, the questionnaire is used to evaluate the scores of a medical student in future planning, occupational health, and teamwork spirit. The compliance evaluation results show that CBL teaching mode can significantly improve the compliance rate of medical students in training and promote the confidence of future role change to a certain extent.