bluuebunny/crossref_metadata_2025_split huggingface dataset:
Anspruch und Wirklichkeit: Umsetzung der G-BA
Qualitätsmanagement-Richtlinie bezüglich der Anwendungspraxis
der OP-Checkliste – Status Quo an einem universitären
Maximalversorger
Authors: Weckenbrock Ralf 
Published: September 2020

ZusammenfassungChirurgische Behandlungspfade können die Entstehung von
Unerwünschten Ereignissen (UE) durch die immanente Komplexität
ihrer Leistungserbringung begünstigen. Die »Surgical Safety
Checklist« (SSC) der Weltgesundheitsorganisation (WHO) ist ein
Instrument, das die perioperative Morbidität und Mortalität
wirksam senkt. Vor diesem Hintergrund hat der Gemeinsame Bundesausschuss (G-BA)
2016 in einer Qualitätsmanagement-Richtlinie (QM-RL) die Anwendung von
OP-Checklisten bei chirurgischen Eingriffen verpflichtend vorgeschrieben. Ziel
der Untersuchung war deshalb, die vergleichende Erfassung der
Checklisten-Compliance an allen 10 chirurgischen Organisationseinheiten der
Universitätsmedizin Mainz in der zweiten Jahreshälfte 2017 und
2018. Neben der Anlage der SSC wurde die Bearbeitung der Unterpunkte
»Sign-In«, »Team-Time-Out« und
»Sign-Out« ausgewertet. Im Vergleich von 2017 zu 2018 zeigten
alle Parameter Steigerungen (»Anlage der Checkliste (94,2 /
96,5%), »Sign-In« (81,4 / 84,4%),
»Team-Time-Out« (56,8 / 62,4%) und
»Sign-Out« (50,7 / 57,9%) ohne statistische
Signifikanz (p>0,05). Demgegenüber ergaben sich signifikante
Unterschiede zwischen zertifizierten und nicht zertifizierten Chirurgischen
Betriebseinheiten. 2017 wiesen die Parameter »Sign-In« (87,9
/ 71,8%; p=0,034), »Team-Time-Out« (68,4
/ 39,4%; p=0,029) und »Sign-Out« (62,1
/ 33,6%; p=0,029) und 2018 das
»Team-Time-Out« (76,2 / 41,7%; p=0,019)
und das »Sign-Out« (71,3 / 37,9%;
p=0,019) signifikante Unterschiede zwischen zertifizierten und nicht
zertifizierten Betriebseinheiten auf. Von 2017 zu 2018 konnte die Implementation
der SCC insbesondere in zertifizierten Einrichtungen gesteigert werden. Demnach
scheint die externe Kontrolle vorgeschriebener Qualitätsmerkmale
z. B. im Rahmen eines Zertifizierungsverfahrens als ein geeignetes
Instrument zur Steigerung der Checklisten-Compliance.
Biofeedback for Pelvic Floor Disorders
Authors: Hite Melissa , Curran Thomas 
Published: September 2020

AbstractDefecatory disorders can include structural, neurological, and functional disorders in addition to concomitant symptoms of fecal incontinence, functional anorectal pain, and pelvic floor dyssynergia. These disorders greatly affect quality of life and healthcare costs. Treatment for pelvic floor disorders can include medications, botulinum toxin, surgery, physical therapy, and biofeedback. Pelvic floor muscle training for pelvic floor disorders aims to enhance strength, speed, and/or endurance or coordination of voluntary anal sphincter and pelvic floor muscle contractions. Biofeedback therapy builds on physical therapy by incorporating the use of equipment to record or amplify activities of the body and feed the information back to the patients. Biofeedback has demonstrated efficacy in the treatment of chronic constipation with dyssynergic defecation, fecal incontinence, and low anterior resection syndrome. Evidence for the use of biofeedback in levator ani syndrome is conflicting. In comparing biofeedback to pelvic floor muscle training alone, studies suggest that biofeedback is superior therapy.
Practice Recommendations for Transcranial Doppler Ultrasonography in Critically Ill Children in the Pediatric Intensive Care Unit: A Multidisciplinary Expert Consensus Statement
Authors: O'Brien Nicole Fortier , Reuter-Rice Karin , Wainwright Mark S. , Kaplan Summer L. , Appavu Brian , Erklauer Jennifer C. , Ghosh Suman , Kirschen Matthew , Kozak Brandi , Lidsky Karen , Lovett Marlina Elizabeth , Mehollin-Ray Amy R. , Miles Darryl K. , Press Craig A. , Simon Dennis W. , Tasker Robert C. , LaRovere Kerri Lynn 
Published: September 2020

AbstractTranscranial Doppler ultrasonography (TCD) is being used in many pediatric intensive care units (PICUs) to aid in the diagnosis and monitoring of children with known or suspected pathophysiological changes to cerebral hemodynamics. Standardized approaches to scanning protocols, interpretation, and documentation of TCD examinations in this setting are lacking. A panel of multidisciplinary clinicians with expertise in the use of TCD in the PICU undertook a three-round modified Delphi process to reach unanimous agreement on 34 statements and then create practice recommendations for TCD use in the PICU. Use of these recommendations will help to ensure that high quality TCD images are captured, interpreted, and reported using standard nomenclature. Furthermore, use will aid in ensuring reproducible and meaningful study results between TCD practitioners and across PICUs.
Dengue-Associated Posterior Reversible Encephalopathy Syndrome
Authors: Manya Sharath M. , Mahalingam Soundarya , Raeesa Fathima , Srivatsav Sathya 
Published: September 2020

AbstractDengue fever has been associated with a myriad of complications, due to widespread inflammation in the various afflicted organs. Central nervous system (CNS) complications include encephalitis, encephalopathy, intracranial bleed, and spinal and cranial nerve involvement with varied outcomes. We report a case of an adolescent girl who presented with dengue fever and significant hypotension requiring intravenous fluids and vasopressors, and developed seizures on the third day of admission. Magnetic resonance imaging (MRI) of brain showed features suggestive of posterior reversible encephalopathy syndrome. She was managed conservatively with antiepileptics. She showed complete clinical recovery over the next 3 days and remained normal with seizure freedom at a recent follow-up after tapering antiepileptics.
Impact of COVID-19 Pandemic on Neurosurgical Practice in a Tertiary Care Center in India
Authors: Singh Rahul , Sahu Anurag , Singh Kulwant , Prasad Ravi Shankar , Pandey Nityanand , Singh Ramit Chandra 
Published: September 2020

Abstract

Objectives The aim of the study is to determine the magnitude of repercussions of coronavirus disease 2019 (COVID-19) pandemic on neurosurgical specialty and formulate a management approach.

Materials and Methods This combined retrospective and prospective study was done in neurosurgical specialty of IMS–BHU, Varanasi, India, a tertiary care center, between January 1, 2020 and May 31, 2020. Analysis of impact on neurosurgical emergency and electives was done over before pandemic, during lockdown 1 and 2 and during lockdown 3 and 4 timelines. Effects of COVID-19 pandemic on psychology of neurosurgical team (50 members) and on patient party (88) were also evaluated. Virtual learning and webinars as a substitute to residential neurosurgical training were analyzed by a questionnaire given to 13 neurosurgeons of our department.

Statistical Analysis Ordinary one-way ANOVA (analysis of variance) and unpaired t-test were used according to data analyzed. p < 0.05 was considered statistically significant. GraphPad Prism software was used for this analysis.

Results On an average 8.22 admissions per day were done in neurosurgical emergency before pandemic. After lockdown these figures reduced to 3.2 admissions per day during lockdown 1 and 2 and to 5.36 admissions per day during lockdown 3 and 4. There was significant reduction in neurotrauma admission rate during lockdown (p < 0.0001) at our center. There was 76% reduction in emergency neurosurgical operated cases during pandemic. There was significant reduction in outpatient department (OPD) attendance per day, OPD admissions per day (p < 0.0001), and total elective surgeries (p < 0.0001) during lockdown. Of 50 neurosurgical team members (neurosurgeons, nursing, and ground staff) interviewed, 90% of them had the fear of contacting the COVID-19 disease, fear of well-being of family and children, and difficulty in transport. Three out of 13 neurosurgeons (23.1%) agreed on change in practice based on what they learned from virtual teaching and webinars and only two of them (15.4%) accepted improvement of skills based on virtual learning.

Conclusion The COVID-19 pandemic is causing a significant impact on health care systems worldwide. For conserving resources elective surgical procedures should be limited. This pandemic has a negative impact on neurosurgical resident training program and psychology of both neurosurgical unit and patients.
Revisiting donkey anaphora in Mandarin Chinese
Authors: Cheng Lisa Lai-Shen , Huang C. -T. James 
Published: September 2020

Abstract
In their article published in this journal, Pan and Jiang (2015)
challenge the claims and proposals made in Cheng and Huang (1996) concerning both the
distributional patterns and interpretive strategies for donkey anaphora in Mandarin conditional. They claim that all three types
of conditionals (rúguǒ-, dōu- and bare conditionals) allow either a wh-phrase or a pronoun in
the consequent clause, and that both the wh-phrase and the pronoun may be either unselectively bound or
interpreted by the E-type strategy. We show that, except for an observation already mentioned and accommodated in Cheng and Huang’s (1996) analysis of rúguǒ-conditionals, their
distributional claims are incorrect. It is also shown that the interpretative flexibility they propose is untenable, as it leaves
a number of otherwise well-predicted properties unaccounted for.
Study of winding vibration and transmission characteristics of three-phase oil-immersed distribution transformer based on FEA
Authors: Wu X W , Zhang Z Z , Zhu L Y 
Published: September 2020

Abstract
In this paper, the magnetic-structure-acoustic multi-physical field model of S13-M400/10 distribution transformer is established through the FEA software. The harmonic response analysis method is used to study the winding vibration and transmission characteristics of the transformer. The simulation results show that the flux leakage distribution of windings on each core column is mainly determined by the current flowing through these windings. The radial and axial acceleration distributions of the windings are U shape and M shape respectively along the winding height. The acceleration of B phase windings is smaller than that of A and C phase windings. The vibration of the oil tank surface is concentrated in its middle and lower part. The tank side vibration is mainly affected by the vibration of the nearest phase windings, while the tank front vibration is affected by the vibration of the three-phase windings together. This study is of great significance for further studies of the vibration characteristics of the transformer under unbalanced load and proposing the vibration reduction and noise reduction measures for the distribution transformer.
Applying Reinforcement Learning for Customer Churn Prediction
Authors: Panjasuchat M , Limpiyakorn Y 
Published: September 2020

Abstract
Customer churn prediction is one of the biggest challenges for companies nowadays. Since the loss of customers directly affects the organization’s reputation, financial and growth plans. Customer behaviours may change due to any uncontrollable factors or unexpected circumstances, resulting in changing patterns of data. This may aggravate the prediction performance of the classifiers generated from supervised learning technique considered as Passive learning. This paper has thus proposed applying the technique of reinforcement learning for customer churn prediction. The model of Deep Q Network (DQN) is implemented and adapted for learning on the selected customer churn dataset used for classification tasks. We simulate a different distribution dataset with shuffle sampling to embrace pattern changes. The performance of the selected classifiers, compared to DQN, has been evaluated with four measures: accuracy, precision, recall, and F1. The results showed that as Active learner, DQN outperformed the selected classifiers, XGBoost, Random forest, and kNN, when data have been enlarged and evolving with emerging new patterns.
A Smart Attendance System for Imam Abdulrahman Bin Faisal University Using Facial Recognition
Authors: Alghamdi Raneem , Alsubaie Wafaa , Alharthi Renad , Alghamdi Wedyan , Alboaneen Dabiah A. , Alqahtani Nourah F. 
Published: September 2020

Abstract
Students’ attendance is one of the methods used to ensure students success by making sure that a student does not miss many classes. The most dominant method used nowadays in the Saudi universities such as, Imam Abdulrahman Bin Faisal University (IAU), is the traditional method where the instructors are the ones responsible for taking student’s attendance. Developing new and effective methods is critical to improve the traditional way and minimise their errors. A proposed facial recognition based attendance system is one efficient method that can substitute the traditional methods. Installing cameras in classrooms where it detects faces and recognise each face for attendance registration is more competent. The system can also track students’ attendance and warn them if they exceeded the permitted absences rate. The proposed system facilitates the attendance registration process and reduces the time and effort for both students and instructors.
Emotion Recognition Algorithm Based on Panorama-plane Mapping Dataset and VGG16 in Prison Monitoring System
Authors: Zhang Zeping , He Jing , Zhang Zhiwei 
Published: September 2020

Abstract
This paper proposes a digital processing scheme for efficient panoramic-plane image mapping for general-purpose panoramic cameras pictures, and builds an efficient emotion recognition algorithm based on VGG16 for real-time monitoring in prison environment. Panoramic-plane mapping algorithm is used to reduce the distortion of the input images and analyse the collected facial data to predict the sentiment of the prisoners. Compared with traditional monitoring methods, this algorithm is able to automatically sense the emotional changes of prisoners, which might improve the situation that traditional prison monitoring requires a large amount of human and material resources. We have proved that the method shows a good result on reducing distortion, besides our method runs with a small computation load so it is optimized to support real-time processing through experiments. The model trained in the experiments has reached a considerable accuracy up-to 79.75% on emotion classification at the same time. It is hopeful that the research could utilize in the future development of unattended prison monitoring.
The Technology of Moving Target Detection and Tracking Based on Sequential SAR Image
Authors: Ying Liu , Long Zhuang , Xin Nie 
Published: September 2020

Abstract
Although the multi-channel SAR-GMTI technology can be used in ground moving target detection, but only can get trace point of the ground moving target, the ground moving target tracking and track reconstruction can’t be achieved. This article presents a new method of ground moving target detection and tracking which is based on sequence SAR images. Firstly, the moving target detection and velocity estimation can be realized using the method of multi-channel processing. Secondly, the location of moving target can be estimated accurately using a high accuracy target location method based on knowledge-aid. The method uses the matching and target tracking technique based on sequential SAR images to realize the tracking and track reconstruction of moving target. Next, the image reference locking technology is used to achieve accurate image registration for a series of sequential SAR images obtained. Finally, the moving target can be tracked. The results of measured data shows the validity of the presented method.
A High Precision Rotating Line Detection Method for the Rotation Angle Measurement Based on Machine Vision
Authors: Cheng Hao , Cai Chenguang , Wang Ying , Liu Zhihua , Yang Ming 
Published: September 2020

Abstract
The accuracy of the rotation angle measurement method based on machine vision with the line as the reference target is limited by line detection accuracy. The Line Segment Detector (LSD) method is a high precision and effective method, but there are detected false lines and discontinuous lines when the LSD method is actually used to detect the rotating lines in the images. In this paper, we adjust three parts of the LSD method: image scaling, gradient magnitude threshold, and aligned points density threshold to detect lines accurately. The high precision detection of the rotating line is obtained by our adjusted method. Besides, the rotation angle measurement accuracy with the lines detected by our adjusted LSD reaches the measurement error level of arcseconds, which proves its effective performance.
Interactive Color Theme Editing System for Interior Design
Authors: Yan Hai , Yang Bin , Li Xueming , Wu Hongyu , Fu Qiang 
Published: September 2020

Abstract
In this paper, we develop a simple yet effective system for interactive indoor scene color theme editing. Our system permits the user to synthesize material/texture with user-specified colors and attaching the synthesized results to the given 3D indoor scenes. Two main improvements are made in this paper. Firstly, we give a new strategy to decompose texture to color, grey texture image and material parameters thus enable the user editing on certain of these items. Secondly, our system is a plus-in unit that integrated into Unity3D. Thus a quick preview of the color theme edited by the user can be rendered in real time. Experiments show that our system can assist the user to create an interior color theme efficiently. Moreover, our system is simple and easy to use, and has good runtime performance.
Bank Direct Marketing Analysis Based on Ensemble Learning
Authors: Hao Ruiting , Xia Xiaoqian , Shen Siyi , Yang Xiaorong 
Published: September 2020

AbstractIn the era of Internet and big data, the bank has gradually realized that the traditional data analysis cannot meet the demands of the existing marketing. So the bank direct marketing based on machine learning emerges. However, there are few references which are completely based on ensemble learning. As different banks have different structures of customer data, the existing model cannot be employed directly. Therefore, this article collects the marketing data of a Portugal’s bank and compares the classification effects of six different models under three ensemble learning algorithms ---“Boosting”, “Bagging” and “Stacking”, respectively. Then we select the most appropriate model which has the best performance as the final classifier. Banks can use the classifier to judge whether a customer will order financial products and make direct marketing plans.
Electrical varieties as vertex integrable statistical models
Authors: Gorbounov Vassily , Talalaev Dmitry 
Published: September 2020

Abstract
We propose a new approach to studying electrical networks interpreting the Ohm law as the operator which solves certain local Yang–Baxter equation. Using this operator and the medial graph of the electrical network we define a vertex integrable statistical model and its boundary partition function. This gives an equivalent description of electrical networks. We show that, in the important case of an electrical network on the standard graph introduced in [Curtis E B et al 1998 Linear Algebr. Appl.
283 115–50], the response matrix of an electrical network, its most important feature, and the boundary partition function of our statistical model can be recovered from each other. Defining the electrical varieties in the usual way we compare them to the theory of the Lusztig varieties developed in [Berenstein A et al 1996 Adv. Math.
122 49–149]. In our picture the former turns out to be a deformation of the later. Our results should be compared to the earlier work started in [Lam T and Pylyavskyy P 2015 Algebr. Number Theory
9 1401–18] on the connection between the Lusztig varieties and the electrical varieties. There the authors introduced a one-parameter family of Lie groups which are deformations of the unipotent group. For the value of the parameter equal to 1 the group in the family acts on the set of response matrices and is related to the symplectic group. Using the data of electrical networks we construct a representation of the group in this family which corresponds to the value of the parameter −1 in the symplectic group and show that our boundary partition functions belong to it. Remarkably this representation has been studied before in the work on six vertex statistical models and the representations of the Temperley–Lieb algebra.
Screening of endophytic bacteria antagonistic against Ustilaginoidea virens in rice
Authors: Cui Yu , Guan Qin-Lan , Gong Ming-Fu , Qiu Jie , Wang Li-Yuan , Yuan Jie , Zhou Ai-Yun 
Published: September 2020

Abstract
Rice false smut (RFS) caused by Ustilaginoidea virens is a major disease in rice-producing areas in China. Endophytic bacteria have prominent advantages in controlling host plant diseases. To screen and obtain the antagonistic bacteria of RFS and effectively control RFS, the antagonistic strains were screened from 45 rice endophytic bacteria by the method of plate pair culture, the antagonistic activity of the fermentation broth of the antagonistic strains was measured, and the RFS field control test was performed. The results showed that 45 strains of rice endophytic bacteria had antagonistic activity against on U. virens, of which 23 strains had an antagonistic band of more than 15 mm. The fermented broth of these 23 antagonistic strains had strong antagonistic activity against on U. virens, of which 17 strains had antagonistic band of more than 20 mm, and 3 of them (REB01, REB32, and REB42) had more than 28 mm. . The three strains (REB01, REB32 and REB42) had 81.48%, 72.05% and 76.76% of respectively field control effect on RFS, which was very significant (P <0.01) higher than the field control effect of 500-fold dilution of 5% Jinggangmycin (61.72%), and showing great potential for biological control of RFS.
Fermentation properties of yogurt with fermented broth of Paecilomyces cicadae
Authors: Xiong Hua , Guan Qin-Lan , Gong Ming-Fu , Zhang Kun-Qi , Zhao Ming , Guo Jing , He Wan-Yue 
Published: September 2020

Abstract
Fermented broth of edible fungus is a product obtained by liquid culture with edible fungus. The yogurt adding fermented broth of edible fungus can promote the growth of lactobacillus in yogurt, increase the total number of lactobacillus in the finished product, give the product special flavor, and have higher nutritional value and new health effects. The changes in pH and lactic acid content during the fermentation, the content of polysaccharides, crude protein, and trace elements, and the changes in the total number of lactobacillus during storage of three types of yogurt, yogurt with fermented broth of Paecilomyces cicadae added (fermented broth yogurt), yogurt with fruit body of P. cicadae added (fruit body yogurt), and yogurt with no flavour added (natural yogurt), were studied. The results indicated that the speed of pH decrease, and increase of lactic acid content of fermented broth yogurt were higher than those of the other two types of yogurt. The lactic acid content of the three yogurts tended to stabilize to a certain time after fermentation. The nutrient content of crude protein, polysaccharide, iron, magnesium, calcium, and zinc of fermented broth yogurt was higher than that of the other two yogurt. During storage, compared with the other two types of yogurt, the total number of lactobacillus in fermented broth yogurt declined more slowly. Fermented broth yogurt of P. cicadae promoted the growth of lactobacillus in yogurt and had high nutritional value.