bluuebunny/crossref_metadata_2025 huggingface dataset:
Management of acute low back pain in emergency departments in São Paulo, Brazil: a descriptive, cross-sectional analysis of baseline data from a prospective cohort study
Authors: Oliveira Indiara Soares , Tomazoni Shaiane Silva , Vanin Adriane Aver , Araujo Amanda Costa , de Medeiros Flávia Cordeiro , Oshima Renan Kendy Ananias , Costa Leonardo Oliveira Pena , Costa Lucíola da Cunha Menezes
Published: April 2022

Objective

To describe management strategies used in public emergency departments in a middle-income country for patients with acute non-specific low back pain.

Design

A descriptive, cross-sectional analysis of baseline data from a prospective cohort study.

Setting and participants

A study with 600 patients with low back pain presenting in four public emergency departments from São Paulo, Brazil was conducted.

Outcome measures

Diagnostic tests, pharmacological interventions, and/or referral to other healthcare professionals were collected. Descriptive analyses were used to report all outcomes.

Results

Of all patients, 12.5% (n=75) underwent some diagnostic imaging tests. Medication was administered to 94.7% (n=568) of patients. The most common medications were non-steroidal anti-inflammatory drugs (71.3%; n=428), opioids (29%; n=174) and corticosteroids (22.5%; n=135). Only 7.5% (n=45) of patients were referred to another type of care.

Conclusion

There is a need for research data on low back pain from middle-income countries. There was an acceptable rate of prescription for diagnostic imaging tests. However, there were high medication prescriptions and small rates of referrals to other healthcare services. Our findings indicate that there is still a need to implement best practices in the management of acute low back pain at public emergency departments in Brazil.
Investigating the association between inpatient stroke therapy and disability, destination on discharge, length of stay and mortality: a prospective cohort study using the Sentinel Stroke National Audit Programme
Authors: Gittins Matthew , Lugo-Palacios David Gibran , Vail Andy , Bowen Audrey , Paley Lizz , Bray Benjamin , Gannon Brenda , Tyson Sarah
Published: April 2022

Objective

‘More is better’ is a recognised mantra within stroke therapy, however, this has been developed in patients receiving long term rehabilitation. We investigated the relationship between amount of therapy received (from therapists and psychologists) and key patient outcomes during inpatient care.

Design

A secondary analysis of data from a prospective cohort study was performed. Multilevel mixed models adjusting for measured confounders (eg, severity), explored the relationship between therapy dose (average minutes per day of stay) and outcomes (disability, length of stay, home at discharge and mortality). Therapy was explored using simple linear terms and flexible natural cubic splines to allow for more complex relationships.

Setting

Data from the Sentinel Stroke National Audit Programme, covering England, Wales and Northern Ireland between July 2013 and July 2015 contained 94 905 adults with a stroke and still an inpatient after 72 hours. These patients received 92% (physiotherapy), 88% (occupational therapy), 57% (speech and language therapy) and 5% (clinical psychology), respectively.

Results

The average amount of therapy, for individual and ‘any’ therapy combined per day of stay was low. Overall, 41% were discharged with an ‘independent’ modified Rankin Scale (≤2), 14% died, 44% were discharged home, and the median length of stay was 16 days. We observed complex relationships between amount of therapy received and outcomes. An additional minute of ‘any’ therapy, occupational therapy, speech and language therapy and clinical psychology was associated with improved outcomes. Conversely, more physiotherapy was also associated with lower mortality and shorter length of stay, but also lower independence and discharge home.

Conclusions

Our findings suggest for stroke inpatients requiring therapy, ‘More is better’ may be overly simplistic. Strong limitations associated with analysis of routine data restrict further robust investigation of the therapy–response relationship. Robust prospective work is urgently needed to further investigate the relationships observed here.
Dioptric power and refractive behaviour: a review of methods and applications
Authors: Rubin Alan , Evans Tanya , Hasrod Nabeela
Published: April 2022

Myopia is a global healthcare concern and effective analyses of dioptric power are important in evaluating potential treatments involving surgery, orthokeratology, drugs such as low-dose (0.05%) atropine and gene therapy. This paper considers issues of concern when analysing refractive state such as data normality, transformations, outliers and anisometropia. A brief review of methods for analysing and representing dioptric power is included but the emphasis is on the optimal approach to understanding refractive state (and its variation) in addressing pertinent clinical and research questions.

Although there have been significant improvements in the analysis of refractive state, areas for critical consideration remain and the use of power matrices as opposed to power vectors is one such area. Another is effective identification of outliers in refractive data. The type of multivariate distribution present with samples of dioptric power is often not considered. Similarly, transformations of samples (of dioptric power) towards normality and the effects of such transformations are not thoroughly explored. These areas (outliers, normality and transformations) need further investigation for greater efficacy and proper inferences regarding refractive error. Although power vectors are better known, power matrices are accentuated herein due to potential advantages for statistical analyses of dioptric power such as greater simplicity, completeness, and improved facility for quantitative and graphical representation of refractive state.
Interleukin-11 drives human and mouse alcohol-related liver disease
Authors: Effenberger Maria , Widjaja Anissa A , Grabherr Felix , Schaefer Benedikt , Grander Christoph , Mayr Lisa , Schwaerzler Julian , Enrich Barbara , Moser Patrizia , Fink Julia , Pedrini Alisa , Jaschke Nikolai , Kirchmair Alexander , Pfister Alexandra , Hausmann Bela , Bale Reto , Putzer Daniel , Zoller Heinz , Schafer Sebastian , Pjevac Petra , Trajanoski Zlatko , Oberhuber Georg , Adolph Timon , Cook Stuart , Tilg Herbert
Published: April 2022

Objective

Alcoholic hepatitis (AH) reflects acute exacerbation of alcoholic liver disease (ALD) and is a growing healthcare burden worldwide. Interleukin-11 (IL-11) is a profibrotic, proinflammatory cytokine with increasingly recognised toxicities in parenchymal and epithelial cells. We explored IL-11 serum levels and their prognostic value in patients suffering from AH and cirrhosis of various aetiology and experimental ALD.

Design

IL-11 serum concentration and tissue expression was determined in a cohort comprising 50 patients with AH, 110 patients with cirrhosis and 19 healthy volunteers. Findings were replicated in an independent patient cohort (n=186). Primary human hepatocytes exposed to ethanol were studied in vitro. Ethanol-fed wildtype mice were treated with a neutralising murine IL-11 receptor-antibody (anti-IL11RA) and examined for severity signs and markers of ALD.

Results

IL-11 serum concentration and hepatic expression increased with severity of liver disease, mostly pronounced in AH. In a multivariate Cox-regression, a serum level above 6.4 pg/mL was a model of end-stage liver disease independent risk factor for transplant-free survival in patients with compensated and decompensated cirrhosis. In mice, severity of alcohol-induced liver inflammation correlated with enhanced hepatic IL-11 and IL11RA expression. In vitro and in vivo, anti-IL11RA reduced pathogenic signalling pathways (extracellular signal-regulated kinases, c-Jun N-terminal kinase, NADPH oxidase 4) and protected hepatocytes and murine livers from ethanol-induced inflammation and injury.

Conclusion

Pathogenic IL-11 signalling in hepatocytes plays a crucial role in the pathogenesis of ALD and could serve as an independent prognostic factor for transplant-free survival. Blocking IL-11 signalling might be a therapeutic option in human ALD, particularly AH.
An assessment of data accuracy and best practice recommendations for observations of lichens and other taxonomically difficult taxa on iNaturalist
Authors: McMullin R. Troy , Allen Jessica L.
Published: April 2022

We assess the identification accuracy of ‘research grade’ observations of lichens posted on the online platform iNaturalist. Our results show that these observations are frequently misidentified or lack the necessary chemical and (or) microscopic information for accurate identification. Lichens are a taxonomically difficult group, but they are ubiquitous and eye-catching and are regularly the subject of observations posted on iNaturalist. Therefore, we provide best practice recommendations for posting lichen observations and commenting on observations. Data from iNaturalist are a valuable tool for understanding and managing biodiversity, particularly at this crucial time when large scale biodiversity decline is occurring globally. However, the data must be accurate for them to effectively support biodiversity conservation efforts. Our recommendations are also applicable to other taxonomically difficult taxa.
Inclusion of recreational fishing in data-limited stocks: a case study on Norway lobster (Nephrops norvegicus) in Norway
Authors: Zimmermann Fabian , Kleiven Alf Ring , Ottesen Merete Vik , Søvik Guldborg
Published: April 2022

Recreational and semi-subsistence fisheries are challenging to monitor but can act as precursors of developments in commercial fisheries, contributing information in data-limited situations. We compared trends in commercial landings of Norway lobster (Nephrops norvegicus) with data collected through a citizen science project by recreational fishers in Norway during a period that coincided with the onset of a commercial trap fishery. The results show that trap fishing for Nephrops emerged recently in Norway, with significant regional differences in size composition and catch rates. Comparable patterns in catch rates between regions were found in commercial landings during the same period, suggesting that landings per boat trip may provide a suitable abundance index in a severely data-limited fishery. Our study indicates that recreational fishing acted as trailblazer for a surge in fishing with lower-impact gear along the Norwegian coast, underscoring the fact that non-commercial fisheries may act as early indicators of emerging commercial fisheries. Collecting information through citizen science projects targeting non-commercial fishers can therefore provide baseline data, especially from the earliest, unmonitored stages of fisheries, and contribute to stock assessment.
Larmor rotation in galaxies
Authors: Ludwig G. O.
Published: April 2022

The role of the gravitomagnetic field in the rotation of galaxies is clarified. Larmor’s theorem simplifies the analysis of different galactic equilibrium solutions. In particular, the self-consistent solution, which takes into account both the equivalent Larmor gravitomagnetic field and fluid convection, recovers previous results that reproduce galactic rotation curves without recourse to dark matter.
Sentence Boundary Disambiguation for Tibetan Based on Attention Mechanism at the Syllable Level
Authors: Li Fenfang , Lv Hui , La Duo , Yong Binbin , Zhou Qingguo
Published: April 2022

Tibetan is a low-resource language with few existing electronic reference materials. The goal of Tibetan
sentence boundary disambiguation (SBD)
is to segment long text into sentences, and it is the foundation for downstream tasks corpora building. This study implemented the Tibetan SBD at the syllable level to avoid
word segmentation (WS)
errors affecting the accuracy of SBD. Specifically, the attention mechanism is introduced based on a
recurrent neural network (RNN)
to study Tibetan SBD. The primary objective is to determine, using a trained model, whether the shad contained in Tibetan text is the ending of the sentence, and implement experiments on syllable embedding and component embedding to measure the model's performance. The highest accuracy for Tibetan syllable embedding and component embedding is 96.23% and 95.40 %, respectively, and the F1 score reaches 96.23% and 95.37%, respectively. The experimental results demonstrate that the proposed method can achieve better results than the established rule-based and statistical methods without considering various syntactic and
part-of-speech (POS)
tagging rules. German and English data from the Europarl corpus and Thai data from the IWSLT2015 corpus are validated to prove the models’ reliability and generalizability. The results demonstrate that this method is efficient not only for low-resource languages but also for high-resource languages. More importantly, we can formally apply the experimental results of this study to the research of downstream tasks, such as machine translation and automatic summarization.
A Female Career in Research
Authors: Flegal Katherine M.
Published: April 2022

After a long career at the National Center for Health Statistics, I retired and joined the Stanford Prevention Research Center as an unpaid associate. I was once described by a former US Food and Drug Administration commissioner as “one of the great epidemiologists.” The chair of the Harvard nutrition department, speaking on National Public Radio, once described my research as “rubbish.” Both may be exaggerations. Here I address some of the events that led to these contrasting descriptions. I also address the extent to which the so-called Matilda effect may have influenced my career. Are women in science on an equal footing with men? The Matilda effect suggests not. Unlike the Matthew effect for scientists, whereby those of higher prestige accrue a disproportionate share of recognition and rewards, the Matilda effect proposes that women scientists are systematically undervalued and underrecognized. I could never get a faculty job and was often treated like an underling. Nonetheless I persevered to publish highly cited research on several high-profile and sometimes controversial topics. Though overt sexism in science and workplaces has diminished over the course of my career, progress toward eliminating unconscious bias has been slower. The Matthew and Matilda effects are still powerful forces that distort incentives and rewards in science.
Effects of Ulinastatin on Myocardial Ischemia-Reperfusion Injury, Cardiac Function, and Serum TNF-α and IL-10 Levels in Patients Undergoing Cardiac Valve Replacement under Cardiopulmonary Bypass
Authors: Wang Hai , Zhang Dafa , Qian Hongbo , Nie Jun , Wei Jun
Published: April 2022

Background. Myocardial ischemia-reperfusion injury (MIRI) is a very common adverse reaction after cardiac valve replacement (CVR) under cardiopulmonary bypass, which seriously affects the rehabilitation and prognosis of patients. Objective. The prevention and treatment of MIRI are a hotspot of modern medical research, and this study is aimed at providing reliable reference and guidance for future clinical prevention and treatment of MIRI by analyzing the effects of ulinastatin (UL) on cardiac function and MIRI of patients after CVR. Methods. A total of 104 patients undergoing CVR under cardiopulmonary bypass in our hospital were selected as research participants. Among them, 52 patients treated with UL were assigned to the observation group, and the rest 52 patients given the same amount of normal saline were assigned to the control group. The cardiopulmonary bypass status, postoperative status, cardiac function, inflammatory response, oxidative stress response, and hemodynamics were observed and compared between the two groups. In addition, clinical efficacy and safety and patient prognosis were compared. Results. Through experimental analysis, we found that UL had no significant effect on the clinical efficacy, safety, and prognosis of patients after surgery (

P
>
0.05

) but had obvious protective effects on cardiopulmonary bypass status, cardiac function, inflammation, oxidative stress, and hemodynamics (

P
<
0.05

). Conclusion. UL can effectively prevent the occurrence of MIRI after CVR under cardiopulmonary bypass, which is worthy of clinical application.
A Travel Mode Identification Framework Based on Cellular Signaling Data
Authors: Chen Jiatao , Xiong Chen , Cai Ming
Published: April 2022

The rapid development of telecommunication network has produced a large amount of spatial-temporal information of mobile phone users. GPS data are typically collected by smartphones apps, which are restricted to small samples of the population. Cellular signaling data (CSD) are usually collected by mobile network operators, which enables researchers to conduct travel behavior analysis of the entire population at a relatively low cost compared to GPS. However, extracting travel mode information from CSD is particularly challenging due to the noise data and low positioning accuracy. This paper proposes a travel mode identification framework based on CSD, which includes data cleansing and travel mode identification. In terms of data cleansing, oscillation sequence and drift data are mainly cleansed. For the oscillation sequence, this paper proposes a detection algorithm based on time window. For the drift data, this paper proposes a detection algorithm based on distance, velocity and frequency. In terms of travel mode identification, the task is divided into two dichotomous problems: motor and non-motor transport identification and public and private transport identification. Each dichotomous problem proposes an algorithm that does not rely on the ground truth dataset for model training. Finally, a ground truth dataset is constructed to verify all algorithms. The result shows that, in terms of data cleansing, the similarity between CSD after cleansing and the actual trajectory according to DTW improved by 101.13% on average. In terms of travel mode identification, the proposed method can achieve similar or even better accuracy than traditional supervised-learning algorithms (94% in motor and non-motor transport identification, 83.5% in public and private transport identification), which can be directly applied to large-scale population analysis scenarios.
Education Teaching Evaluation Method Aided by Adaptive Genetic Programming and Robust Scheduling
Authors: Sun Zhuo , Zhang Shuang , Liu Mairu
Published: April 2022

Process mining technology aims to automatically generate process models by analyzing events, thereby assisting the design and redesign of process models. Although many process mining methods have appeared, they all have deficiencies. These methods focus on mining from the behavioral aspects described by the log, while ignoring the structural nature of the process model itself. The complexity of the process describes the simplicity and ease of understanding of the process. Higher process complexity affects the readability of the process. Genetic programming has strong robustness. Its individual representation based on tree structure can describe the special structure of the process. The introduction of process complexity fitness enables it to consider the complexity of the process model itself while mining log behavior, so as to achieve nonlinear mining of complex processes. This paper analyzes the process mining based on genetic programming and proposes process individuals based on tree structure. By realizing the combination of process complexity measurement and process mining technology, noncomplex process mining can be realized. In this paper, the process complexity is combined with the process mining algorithm based on genetic programming, and a measure of process structural complexity is proposed, which is converted into complexity fitness and introduced into the fitness function of genetic programming, to realize the use of genetic programming. The research results show that the improved new adaptive genetic programming robust scheduling algorithm provides a new idea and method for the evaluation of college sports under different sports conditions. This makes the college sports evaluation management system more intelligent and improves the rational allocation of physical education teaching.
Impact of Ferromagnetic Nanoparticles Submerged in Chemically Reactive Viscoelastic Fluid Transport Influenced by Double Magnetic Dipole
Authors: Kousar N. , Nofal Taher A. , Tahir W. , Bilal S. M. , Sene Ndolane
Published: April 2022

The present article summarized the effects of double magnetic dipole for chemically reactive viscoelastic fluid in the presence of two different ferromagnetic particles, namely, nickel zinc ferrite (NiZnFe2O4) and magnetite ferrite (Fe3O4). Due to double magnetic dipole, an external magnetic field is applied normal to the flow. Blood is used as base fluid due to its viscoelastic fluid properties. The Cattaneo‐Christov heat flux model is used for heat transport phenomena. The physical model is formulated in the form of partial differential equations which are then converted into ordinary differential equations using the suitable transformations. The system is solved numerically using shooting method along with Runge‐Kutta‐Fehlberg method. The characteristics of different parameters like the strength of homogeneous‐heterogeneous reactions (k1 and k2), ferrohydrodynamic interaction (β1), Schmidt number (Sc), Deborah number (α1a), and thermal relaxation time (α1c) on velocity, temperature, and concentration profiles are analyzed through graphs and in tabular form. It has been observed that as magnetic dipole creates a force which attracts the ferrite particles, hence, it slows down the velocity profile. Concentration field depresses due to the presence of strength of heterogeneous reaction parameter k2.It is also noted that by expanding values of thermal relaxation time (α1c), the temperature profile shows a reverse behavior.
Wideband Patch Antenna with Shorting Vias
Authors: Chen Xue , Dou Haipeng
Published: April 2022

A novel patch antenna with three resonant modes is proposed for wideband applications. By introducing the ring slot on the circular patch, the TM02 mode of the smaller circular patch and the TM02 mode of the annular ring can be excited. Also, compared with the traditional circular patch with shorting vias, four components of shorting vias are distributed nonuniformly on the edge of the proposed patch antenna, which can generate another new resonance mode. By merging the three resonant modes, the impedance bandwidth of the antenna is expanded. Meanwhile, the gain of the antenna is enhanced in the wide operating band. The results illustrate that the antenna can operate in the 5.8 GHz ISM band. Its −10 dB impedance bandwidth is from 5.06 to 6.99 GHz, and the relative bandwidth reaches 32%. In addition, the maximum gain of 5.3 dBi is obtained at 6.7 GHz.
Estimating System Reliability Using Neoteric and Median RSS Data for Generalized Exponential Distribution
Authors: Hassan Amal S. , Elshaarawy Rasha S. , Onyango Ronald , Nagy Heba F.
Published: April 2022

In this work, we show how to estimate stress strength (SS) reliability when the stress (Y) and strength (X) distributions are generalized exponentials with a common scale parameter. The SS reliability estimator is considered in view of neoteric ranked set sampling (NRSS) and median ranked set sampling (MRRS). We acquire an estimate of the reliability (R) when such samples of the stress and strength random variables are gathered using the same NRSS technique. Furthermore, the reliability estimator is derived when the stress distribution data are in the pattern of MRSS with just an odd/even set size and the strength distribution data are derived from NRSS and vice versa. The simulation results are used to evaluate and understand the adequacy of a variety of estimators for the suggested schemes. Based on our simulated results, we found that NRSS-based stress strength reliability estimates are more efficient than MRSS-based stress strength reliability estimates. The analysis of real-world data is used to implement the recommended estimators.
Approach to Multiattribute Decision-Making Problems Based on Neutrality Aggregation Operators of Picture Fuzzy Information
Authors: Javed Mubashar , Javeed Shumaila , Ahmad Jihad , Ullah Kifayat , Zedam Lemnaouar
Published: April 2022

This manuscript is aimed at developing some novel operational laws named scalar neutrality operation and neutrality addition on picture fuzzy numbers (PFNs). The main focus of this work is to involve the neutral behaviour of the experts towards the priorities of entities where it presents equal degrees to independent membership functions. Moreover, based on these operations, some novel aggregation operators are established to aggregate the different priorities of experts. Some useful relations and characteristics are examined thoroughly. Lastly, the multiattribute group decision-making algorithm in accordance with the suggested operation is illustrated and examined a case study in order to choose a suitable mining company for a mining project along with several numerical examples. The advantages, as well as the superiority of the suggested approach, are exhibited by comparing the results with a few existing methods.
Botox (OnabotulinumtoxinA) for Treatment of Migraine Symptoms: A Systematic Review
Authors: Shaterian Negar , Shaterian Negin , Ghanaatpisheh Aref , Abbasi Farnaz , Daniali Sara , Jahromi Maryam Jalali , Sanie Mohammad Sadegh , Abdoli Amir
Published: April 2022

Background. Migraine is one of the most common types of headache, and it is the second most common cause of neurological disorders, with an annual prevalence of about 15% of the population. This study aimed to evaluate the effect of BoNT-A on the duration and intensity of migraine attacks. In addition, we investigated the effective injection sites. Methods. According to the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines, we searched online databases, including Web of Science, PubMed, EMBASE, Scopus, Cochrane Library, ProQuest, ClinicalTrials.gov, and Google Scholar from 2011 to 2021. Results. A total of 24 articles were included in the study. The use of BoNT-A in individuals suffering from chronic migraine (CM) decreases the frequency of migraine attacks per month, pain intensity, medication use, emergency visits, and migraine-related disabilities. The BoNT-A was well tolerated and leads to improved performance and better quality of life (QoL). Overall, treatment with BoNT-A in adults with CM is beneficial. In addition, the use of BoNT-A in individuals with vestibular migraine (VM) reduces the frequency of migraines and brings about the improvement of disability status caused by migraine headaches. Meanwhile, the use of BoNT-A reduces the frequency of migraine attacks per month among individuals with chronic refractory migraine (CRM). Conclusions. The use of BoNT-A is a low-cost option for the treatment of various kinds of migraines, including chronic, episodic, unilateral, and vestibular types. BoNT-A can reduce the frequency of migraine attacks per month and diminish the severity of pain.
Research on Shield Tunnelling Parameters Correlation in Composite Strata
Authors: Guo Ziqi , Zhang Huipeng , Shi Xiaoyang , Huang Zhi , Xu Yiyong , Zhang Zhiqiang
Published: April 2022

Shield tunnelling has become the development direction of tunnel construction due to its safety, economy, and speed. The complex formation has complicated geological changes, including soft rock, hard rock, and soft and hard inhomogeneous formation. It is particularly difficult to select and control the tunnelling parameters in shield tunnelling, while the reasonable selection and control of the tunnelling parameters play an important role in the excavation efficiency, tool wear, and surface settlement. Based on the tunnel project between the Dinggong Road North Station and the People’s Park Station online 4 of Nanchang Metro during shield tunnelling construction, this paper collects thrust, torque, and revolution speed of the cutterhead during shield tunnelling in the complex strata with differentiated argillaceous siltstone and gravel and analyzes these parameters by means of mathematical statistics analysis, in order to explore the interrelationship between shield tunnelling parameters under different stratigraphic conditions and put forward optimization suggestions for tunnelling parameters, which can provide a reference for control of tunnelling parameters of earth pressure shield in composite strata.
Effect of the Kanghuier Transparent Hydrocolloid Dressing in Preventing Central Venous Catheter Infection and Phlebitis after Cardiac Surgery
Authors: Han Xiaoling , Li Jiayi , Zeng Ping , Luo Chunfeng , Zhou Dongmei
Published: April 2022

Background. As cardiac surgery is complicated, time-consuming, and traumatic, it may cause great damage to the patient’s body. Therefore, postoperative indwelling venous catheters are required for hemodynamic monitoring and rapid fluid replenishment. Intravenous catheterization infection can easily lead to phlebitis, which not only affects the success of the operation and patient recovery but may also lead to death in severe cases. Good perioperative care is key to reducing postoperative infection in patients, and the choice of dressings for patients with catheterization plays an important role in reducing catheter infection. Objective. The Kanghuier transparent hydrocolloid dressing is known to effectively prevent and treat wound infections. This study is aimed at exploring whether it can reduce the incidence of postoperative catheter infection and phlebitis in patients undergoing cardiac surgery. Methods. A total of 196 patients undergoing cardiac surgery in the Department of Cardiothoracic Surgery of Zhuhai People’s Hospital (Zhuhai Hospital Affiliated with Jinan University) from January 2020 to June 2020 were selected. Among them, 98 patients receiving Kanghuier transparent dressing intervention were selected as group A, and the remaining 98 patients receiving traditional sterile gauze intervention were selected as group B. The incidence of infection and related complications, phlebitis, inflammatory factors, pain at the infusion site, nursing comfort and satisfaction, and quality of life were analyzed and compared between the two groups. Results. It was found that compared with group B, the postoperative central venous catheter infection rate and the incidence of phlebitis were significantly lower in group A. In addition, the inflammatory response of patients in group A was better relieved. Moreover, the nursing comfort and satisfaction and the quality of life of patients in group A were significantly improved. Conclusion. This study suggests that the Kanghuier transparent hydrocolloid dressing is effective in the prevention and treatment of central venous catheter infection and phlebitis in patients after heart surgery.
Real-Time Footprint Planning and Model Predictive Control Based Method for Stable Biped Walking
Authors: Wang Song , Piao Songhao , Leng Xiaokun , He Zhicheng , Bai Xuelin , Huazhong Li
Published: April 2022

In order to walk in a physical environment, the biped will encounter various external disturbances, and walking under persistent conditions is still challenging. This paper tries to improve the push recovery performance based on capture point (CP) and model predictive control. The trajectory of zero moment point (ZMP) and center of mass are solved and predicted in a limited time horizon. Online footprint generator is combined with MPC walking pattern generation, which can keep biped stable in the next few steps, and projection of ZMP is used to calculate the next footprint and reach the target CP in an incremental way. Verification of the proposed stable biped walking method is conducted by simulation and experiments.
Digital Workflow for Immediate Implant Placement and Chairside Provisionalization in the Esthetic Zone
Authors: Donker Vincent J. J. , Raghoebar Gerry M. , Vissink Arjan , Meijer Henny J. A.
Published: April 2022

Introduction. Immediate implant placement and immediate chairside provisionalization in the esthetic zone require meticulous treatment planning. A digital workflow that combines intraoral scans and a cone beam computed tomography scan can be used to visualize the surgical and restorative aspects of the treatment and to plan a prosthetically driven implant position. A digital workflow in implant dentistry enables the prefabrication of an individualized CAD/CAM temporary restoration, based on the planned implant position. This could be a predictable method to deliver a screw-retained temporary restoration, directly after static computer-assisted immediate implant surgery. Interventions. Three patients with a failing tooth in the maxillary esthetic zone were treated with immediate implant placement and chairside provisionalization using this digital workflow. After 3 months, a final restoration was placed. Clinical, radiographic, and patient-reported outcome measures were collected prior to implant treatment, 6 weeks after placing the temporary restoration and then 1 month and 1 year after placing the final restoration. Outcomes. At the 1-year follow-up, healthy soft tissues were observed, and peri-implant bone levels were stable. Patient satisfaction after the treatment was high. Conclusion. The three reported cases demonstrate the potential for predictable immediate implant placement and chairside provisionalization using a digital workflow.
Modeling Spatial Riding Characteristics of Bike-Sharing Users Using Hotspot Areas-Based Association Rule Mining
Authors: Sun Chao , Lu Jian
Published: April 2022

This study aims to investigate the spatial riding characteristics under different demand scenarios using association rule mining with hotspot detection, and to establish the subordinate rules between bike-sharing demand and land elements and between land elements. To reduce deviation from modifiable areal unit problem (MAUP) and improve objectivity and accuracy, we impose spatial constraints using the hotspot detection model instead of the square grid and traditional traffic zone. The bike-sharing trajectory-based kernel density algorithm is employed to explore the optimum analysis locations and the analysis areas with the relatively high demand. More importantly, the research featured here involves five demand scenarios for the differentiation of riding characteristics. The results show that the most significant influencers on bike-sharing demand include financial insurance facilities, dining facilities, and landscapes. As for characteristics of riding destination, the combinations between landscapes and financial insurance facilities, between landscapes and companies/enterprises, and between companies/enterprises and financial insurance facilities are more likely to be visited simultaneously. These findings make us understand urban spatial structure in response to traffic plan and provide evidence for bike-sharing dispatch optimization.
Induction Machine Bearing Fault Detection Using Empirical Wavelet Transform
Authors: Lopez-Gutierrez Ricardo , Rangel-Magdaleno Jose de Jesus , Morales-Perez Carlos Javier , García-Perez Arturo
Published: April 2022

The detection of faults related to the optimal condition of induction motors is an important task to avoid the malfunction or loss of the motor, thus avoiding high repair or replacement costs and faults in the efficiency of the process to which they belong. These faults are not limited to a single area; mechanical and electrical problems can cause a fault. Specifically, the bearing of a motor is subjected to several effects that cause bearing faults, which cause significant breakdowns in the machinery. This article proposes a methodology for detecting bearing faults on an induction motor. The first part of the methodology uses a signal processing method called empirical wavelet transform (EWT), which decomposes the vibration signal into multiple components to extract a series of amplitude and frequency modulated components (AM-FM) with a Fourier spectrum. First, the vibration signal data are collected in a normal operating condition and the other with bearing damage due to perforation. Then, three types of goodness-of-fit tests are used, Kuiper, Kolmogorov–Smirnov, and Pearson chi-square, to classify the signals and determine which ones belong to a damaged engine. Finally, the experimental results show that the EWT in conjunction with the proposed goodness tests achieves competitive precision and efficiency in diagnosing induction motor-bearing faults.
Determinants of Weight Gain among Adult Tuberculosis Patients during Intensive Phase in Debre Markos Town Public Health Facilities, Northwest Ethiopia, 2020: Unmatched Case-Control Study
Authors: Meselu Belsity Temesgen , Demelie Birhanu Barud , Shedie Tigist Adeb
Published: April 2022

Background. Ethiopia is one of the highest tuberculosis burden countries globally, and tuberculosis is one of the most pressing health problems nationally. Weight gain during treatment is the main indicator of good treatment outcome, but there is no adequate information regarding the factors that affect weight gain in Ethiopia. Objective. The objective of this study was to identify determinants of weight gain among adult tuberculosis patients during the intensive phase, in Debre Markos town public health institutions Northwest Ethiopia, 2020. Methods. Unmatched case-control study was conducted in Debre Markos town public health facilities with a total sample size of 236. Cases (clients who got weight) and controls (clients who did not get weight) were enrolled in the study consecutively, and data were collected using standardized questionnaires. Data were entered through Epi-Data version 4.2 and exported to SPSS version 25 for analysis. Bivariable analysis was done, and all independent variables that had

p
<
0.25

were entered into multivariable binary logistic regression analysis. Finally, independent variables which were significantly associated with weight gain at

p
<
0.05

were considered determinant factors of weight gain. Result. Pulmonary tuberculosis (AOR: 5 (95% CI: 2.3, 11.2)), monitoring by health professionals (AOR: 3.7 (1.6, 8.4)), ≥18.5 baseline body mass index (AOR: 3.4 (95% CI: 1.6, 7.3)), parasitic disease (AOR: 3.2 (95% CI: 1.3, 7.99)), <30 days duration of illness before start of treatment (AOR: 2.8 (95% CI: 1.2, 6.1)), and human immune virus/acquired immune deficiency syndrome (AOR: 3.3 (95% CI: 1.2, 9.1)) were independently associated with weight gain compared to their counterpart. Conclusion. Type of tuberculosis, monitoring by health professionals, baseline status, parasitic disease, duration of illness before start of treatment, and human immune virus/acquired immune deficiency syndrome were with the determinants of weight gain. Therefore, early detection, support and supervision, and attention for comorbidity are mandatory during antituberculosis treatment.
Federated Learning Algorithms to Optimize the Client and Cost Selections
Authors: Alferaidi Ali , Yadav Kusum , Alharbi Yasser , Viriyasitavat Wattana , Kautish Sandeep , Dhiman Gaurav
Published: April 2022

In recent years, federated learning has received widespread attention as a technology to solve the problem of data islands, and it has begun to be applied in fields such as finance, healthcare, and smart cities. The federated learning algorithm is systematically explained from three levels. First, federated learning is defined through the definition, architecture, classification of federated learning, and comparison with traditional distributed knowledge. Then, based on machine learning and deep learning, the current types of federated learning algorithms are classified, compared, and analyzed in-depth. Finally, the communication from the perspectives of cost, client selection, and aggregation method optimization, the federated learning optimization algorithms are classified. Finally, the current research status of federated learning is summarized. Finally, the three major problems and solutions of communication, system heterogeneity, and data heterogeneity faced by federated learning are proposed and expectations for the future.
A Novel Model of Network Ideological Education in Universities Based on Learning Analysis for the Era of 5G Mobile Computing
Authors: Yuan Jiefei
Published: April 2022

Internet 5G introduces new methods and carriers for NIE (network ideology education) and marks a new milestone in multicarrier linkage and multichannel university NIE education, combining the benefits of emerging and traditional media. The specific intervention strategies for college students’ online learning procrastination are calculated in this paper, and a learning analysis-based implementation framework for college students’ online learning procrastination intervention is built. The

K

-means algorithm is used to analyze learning style; additional contextual information, such as student-knowledge point mastery and lesson-knowledge point, is added using the CF (collaborative filtering) algorithm, and students’ mastery is predicted using the excavated learning path. Experiments show that adding more data improves the prediction effect, especially in terms of operation efficiency. At the same time, the proposed framework can not only dynamically assess students’ knowledge mastery but also facilitate systematic review feedback and learning order adjustment, as well as provide personalized learning services.
Research on Subsidy Strategy of Shared Accommodation Platform under the Background of Big Data Based on Evolutionary Game
Authors: Xiao Meng , Zhai Chang
Published: April 2022

To attract customers and landlords to join the platform is an important problem to be solved when expanding the size of the shared accommodation platform, and subsidy policies have been proven to be an effective approach in many areas of sharing. In order to analyze the strategies of all parties in the subsidy policy of the shared accommodation platform, a three-party evolutionary game model of shared accommodation platform, consumers, and landlords was built. The strategy stability of each game subject was analyzed, and the equilibrium point stability was explored based on Lyapunov’s method. The game model and influencing factors were simulated and analyzed by MATLAB 2016. Results demonstrated that the consumers and landlords were promoted to join the shared accommodation platform by increasing subsidies to consumers and landlords and reducing consumers’ time costs and landlords’ service fees from the early stage to the rapid development stage of the shared accommodation platform; with the increase of the proportion of landlord’s share in expenses and the decrease of the opportunity loss of platform nonsubsidizing, the strategy of the platform gradually evolves from subsidy to nonsubsidy. The conclusions of this study provide guidance for the mature path of the shared accommodation platform and also give suggestions for the development of the sharing economy.
Multisensor Data and Cross-Validation Technique for Merging Temporal Images for the Agricultural Performance Monitoring System
Authors: Maddala Venkata Kanaka Srivani , Jayarajan K. , Braveen M. , Walia Ranjan , Krishna Patteti , Ponnusamy Sivakumar , Kaliyaperumal Karthikeyan
Published: April 2022

Many approaches for crop yield prediction were analyzed by countries using remote sensing data, but the information obtained was less successful due to insufficient data gathered due to climatic variables and poor image resolution. As a result, current crop yield estimation methods are obsolete and no longer useful. Several attempts have been made to overcome these difficulties by combining high precision remote sensing images. Furthermore, such remote sensing-based working models are better suited to extraterrestrial farmers and homogeneous agricultural areas. The development of this innovative framework was prompted by a scarcity of high-quality satellite imagery. This intelligent strategy is based on a new theoretical framework that employs the energy equation to improve crop yield predictions. This method was used to collect input from multiple farmers in order to validate the observation. The proposed technique’s excellent reliability on crop yield prediction is compared and contrasted between crop yield prediction and actual production in different areas, and meaningful observations are provided.
Intelligent Identification Method of Crop Species Using Improved U-Net Network in UAV Remote Sensing Image
Authors: Liu Zhixin , Su Boning , Lv Fang
Published: April 2022

Aiming at the problems of incomplete classification features extraction of remote sensing images and low accuracy of crop classification in existing crop classification and recognition methods, a crop classification and recognition method using improved U-Net in Unmanned Aerial Vehicle (UAV) remote sensing images is proposed. First, the experimental data set is preprocessed. The data set is expanded by flipping transformation, translation transformation, and random cutting, which expands the number of data sets, and then the original image is cut to meet the requirements of the experiment for image size; Moreover, the network structure of U-Net is deepened, and the atrous spatial pyramid pooling (ASPP) structure is introduced after the encoder to better understand the semantic information and improve the ability of model mining data features; Finally, in order to prevent the overfitting of the deepened model, the dropout layer is introduced to weaken the joint adaptability between various neurons. Experiments show that the comprehensive OA and Kappa indexes of the proposed crop classification and recognition method based on improved U-Net are 92.14% and 0.896, respectively, which are better than the comparison methods. Therefore, the proposed method has good ability of crop classification and recognition.
A Novel Smartphone-Based Color Test for Detection of Color Vision Defects in Age Related Macular Degeneration
Authors: Karampatakis Vassilios , Almaliotis Diamantis , Karamitopoulos Leonidas , Kalliris George , Almpanidou Stavroula
Published: April 2022

Purpose. To evaluate the efficacy of the smartphone-based K-color test to detect color defects in patients with Age-related Macular Degeneration (AMD). Methods. 88 patients (n = 135 eyes) with AMD and 28 controls (n = 53 eyes) underwent color testing with the Hardy–Rand–Rittler (H-R-R), the K-color test, and the Ishihara test. The K-color test presents randomized colored shapes in decreasing steps of intensity, providing also a record system for result tele-transmission. Sensitivity, specificity, and reliability were examined to investigate the validity of the novel test. 26 participants with AMD also completed a questionnaire regarding the feasibility of the test. Results. Linear mixed-effects models indicated a significant difference (

p
<
0.001

) between AMD and normal eyes. The areas under the curve (AUC) were estimated to be 0.897 [95% CI: 0.841–0.952], 0.943 [95% CI: 0.901–0.984], and 0.931 [95% CI: 0.886–0.977] for the red, green, and blue color, respectively. Based on the H-R-R, the sensitivity of the test was 0.79, 0.90, and 0.95 for the red, green, and blue colors, respectively, and specificity was 0.88 for all colors. The new test recognized more abnormal cases than the Ishihara (sensitivity of 0.98 and 1.0 and specificity of 0.48 and 0.38 for red and green colors, respectively). Test-retest reliability was found to be high for the red [ICC = 0.996 (0.990–0.999)], green [ICC = 0.974 (0.929–0.990)], and blue [ICC = 0.992 (0.981–0.997)] colors. The majority of the asked participants stated that they could easily perform the test. Conclusion. The K-color test was found to be sensitive and specific in detecting color defects in AMD patients. The K-color test may serve as a useful tool both for patients and their physicians.