bluuebunny/crossref_metadata_2025_split huggingface dataset:
Spinal erector spinalis block for postoperative analgesia for transfemoral amputation in an ontologic patient: Case Report
Authors: GRIJALVA MARIANA CAROLINA GONZÁLEZ , NUÑO JACQUELINE MORALES 
Published: August 2022

Abstract
Post-surgical pain management during the first 24 hrs before a supracondylar amputation is difficult to control, so the use of multimodal analgesia is essential, regional anesthesia is increasingly used as part of this. The ESP block was described in 2016 by Mauricio Forero for analgesia at thoracic level in patients with chronic neuropathic pain as well as for post-surgical and post-traumatic pain also at thoracic level, in this case we demonstrate a correct and novel use for post-surgical analgesia for a lower limb procedure by placing it at lumbar level. We describe the successful use of single-dose erector spinae plane blockade (ESP) as part of postoperative analgesic management in a patient who underwent transfemoral amputation. ESP was shown to produce sensory blockade in several dermatomes and successful analgesia for the first 72 hr post-surgery.
Modelling the effectiveness of surveillance based on metagenomics in detecting, monitoring, and forecasting antimicrobial resistance in livestock production under economic constraints
Authors: Apenteng Ofosuhene O. , Aarestrup Frank M. , Vigre Håkan 
Published: August 2022

Abstract
Current surveillance of AMR is mostly based on testing indicator bacteria using MIC panels. Metagenomics has the potential to identify all known ARGs in complex samples and thereby detect changes in the occurrence earlier. Here, we simulate the results of an AMR surveillance program based on metagenomics in the Danish pig population. We modelled both an increase in the occurrence of ARGs and an introduction of a new ARG in a few farms and subsequent spread to the entire population. To make the simulation realistic, total cost of the surveillance was constrained, and the sampling schedule set at one pool per month with 5, 20, 50, 100, or 200 samples. Our simulations demonstrate that a pool of 50–100 samples and a sequencing depth of 250 million fragments resulted in the shortest time to detection in both scenarios, with a time-delay to detection of change of \(>\)15 months in all scenarios. Overall, our findings suggest that using metagenomics could improve the monitoring of AMR in the animal population.
To summarise the approach to and findings of the PPIE undertaken as part of a programme of secondary research with a vulnerable, hard to reach population during the COVID-19 pandemic
Authors: McGrane Niall , Dunbar Paul , Keyes Laura M 
Published: August 2022

Abstract
BackgroundPublic and patient involvement and engagement (PPIE) is an important part of research. The inclusion of PPIE in research is becoming more widespread, however, there are some areas where it is still uncommon. For example, undertaking PPIE in secondary analysis projects is uncommon and PPIE with difficult to reach populations and vulnerable groups can be seen as being too difficult to facilitate. The aim was to summarise the approach to and findings of the PPIE undertaken as part of a programme of secondary analysis with a vulnerable, hard to reach population; residents of residential care facilities (RCFs), during the COVID-19 pandemic. MethodsAs part of a project to develop a publically available database of statutory notifications of adverse events from RCFs in Ireland, residents (n=9) from RCFs for older people and people with disability were telephone interviewed. Residents were engaged through gatekeepers and posted participant information and consent forms. Themes were identified using content analyses of interview notes. ResultsThree parent themes were identified, each with two subthemes: privacy concerns, enthusiasm and dissemination of research findings. Residents highlighted the importance that no personal information be shared in the database. Once data were anonymized, residents thought that the database should be published and shared. Residents reported being happy about research being undertaken using the data and thought that publishing the database would help inform the public about RCFs. Completing a PPIE project with a vulnerable group during the global COVID-19 pandemic required planning and resources. Resources included finances, time and expertise. ConclusionsThe involvement of residents informed the data inclusion in the published database and the approach taken in the protection of personal data. Enthusiasm for publication and research using the database by residents enthused the developers as it was considered something that was wanted by residents. The benefits of PPIE can be achieved with vulnerable groups during unprecedented times with the appropriate planning. It requires dedication of time, finances and expertise. Overcoming the obstacles was achievable and worthwhile. The approach outlined can be used as an example to support PPIE in secondary analysis projects and or with vulnerable groups
Customer requirements analysis in PSS design
Authors: Lyu Feng , Feng Zhuangzhuang , Li Fengjun , Su Jianxin 
Published: August 2022

Abstract
The identification of customer requirements (CRs) priority is the beginning of Product-service system (PSS) design, which identifies the direction of enterprise resource allocation. In order to accurately reflect customer’s intrinsic requirements in PSS design, a hierarchical model based on the means-end chain theory is constructed to capture CRs from the perspective of customer expectations in this paper, and then a method combining cloud model, fuzzy Decision-making Trial and Evaluation Laboratory (DEMATEL) with improved analytical Kano (A-Kano) model is proposed to identify importance priority. Cloud model and Relative Preference Relation of the triangular fuzzy number are applied to identify the basic importance with solving the problem of fuzziness and randomness in expert evaluation information. Considering the directional influence relationship among CRs, the fuzzy DEMATEL method is introduced to modify the basic importance. Based on the category criterion of CRs, an improved A-Kano model is constructed, and the importance index and satisfaction index based on customer satisfaction are introduced to identify the final importance. A case study is carried out to verify the scientificity and feasibility of the proposed method.
SIES epidemic model for novel COVID-19 by Conformable fractional derivative
Authors: Sadabadi Negar Bakhshi , Maheri Fariba 
Published: August 2022

Abstract
In this paper, we provide a SIES epidemic model for the spread of COVID-19 using the Conformable fractional derivative. The feasibility region of the system is investigated. We proved the existence of a unique solution for the model by using fixed point theorem. The stability analysis is in the frame of Ulam-Hyers criteria. Numerical simulations are given to support the theoretical results. The results show that the present procedure is very effective and convenient.AMS (2010) subject classification: 49J15, 47H07.
Identification of valid anatomical landmarks to locate and protect recurrent laryngeal nerve during thyroid surgery: A cadaveric study
Authors: Patra Apurba , Asghar Adil , Chaudhary Priti , Ravi Kumar Satish 
Published: August 2022

AbstractPurpose Recurrent laryngeal nerve (RLN) is the most critical structure in terms of intricacy. Anatomic variations of the nerve may further make thyroid surgery cumbersome. The present study was undertaken to provide comprehensive knowledge about the soundness of commonly used anatomical landmarks such as Berry's ligament (BL), tracheoesophageal groove (TEG), inferior thyroid artery (ITA) and the midpoint of the posterior border of the thyroid gland in the identification of the nerve intraoperatively. Methods Thirty adult cadavers were dissected to identify the RLN in the neck and to locate it in relation to the aforementioned anatomical landmarks. Results The RLN/BL relationship: RLN was most often located superficial to the BL (88.3%), followed by deep to the BL in 8.4%, and piercing the BL in 3.3% of cases, respectively. The RLN/TEG relationship: the RLN was located inside the TEG in most cases (71.7%), followed by RLN lying outside the TEG in 28.3%. Outside the groove, it was most commonly found lateral to the TEG (64.7%). RLN/ITA relationship: the nerve was passing deep to the artery in most of the cases (65%), followed by superficial (30%) and rarely (5%) in-between the branches. RLN/ midpoint posterior border of thyroid relationship: In 57 (95%) cases, RLN was coursing in the area posterior to the midpoint of the posterior border of the gland with an average distance of 4.95 ± 2.23 mm ranging between 2.21mm to 12.1mm. Conclusions Both the BL and TEG are potentially crucial for safeguarding RLN. Although in results, BL turns out to be more consistent than TEG, we propose the utilization of both these anatomical landmarks together for complication-free neck surgeries. Furthermore, the midpoint of the posterior border of the thyroid turns out to be the single most consistent landmark for identifying RLN during partial thyroidectomy.
A New Chaos-based Text Encryption/Decryption to Secure Cloud Computing
Authors: Chaouch Ismehene , Naanaa Anis , ElAsmi Sadok 
Published: August 2022

Abstract
In this paper, an analysis study of two encryption algorithms applied to texts is carried out in order to evaluate their robustness in terms of security. The first is the classical cryptosystems known as, respectively, Advanced Encryption Standard (AES) and Data Encryption Standard (DES). The second comes from the study of chaotic systems by using the Tent map. Experimental results and their analysis show that chaotic encryption algorithm is more secure and high efficiency compared to classical algorithms. In addition, the chaotic system present a good encryption speed.
Enlarged perivascular spaces are associated with decreased brain tau deposition
Authors: Kang Koung Mi , Byun Min Soo , Yi Dahyun , Lee Kyung Hoon , Kim Min Jung , Ahn Hyejin , Jung Gijung , Lee Jun-Young , Kim Yu Kyeong , Lee Yun-Sang , Sohn Chul-Ho , Lee Dong Young 
Published: August 2022

Abstract
Background
The drainage of interstitial fluid into the perivascular spaces is recognized as an important clearance pathway for waste from the brain. Nevertheless, the relationship between enlarged perivascular spaces (EPVS) and the key protein pathologies of Alzheimer’s disease, that is, beta-amyloid (Aβ) and tau deposition, has not been clearly understood. We aimed to investigate the associations of EPVS in the BG and CSO with Aβ and tau deposition in older adults with a diverse cognitive spectrum.
Methods
A total of 163 (68 cognitively normal and 95 cognitively impaired) older participants underwent clinical assessment, [11C] Pittsburgh Compound B and [18F] AV-1451 PET, and MRI. EPVS in the BG and CSO were rated using a validated visual rating scale and categorized as low or high degree. Other small vessel disease markers, such as white matter hyperintensities, lacunes, and deep and lobar microbleeds, were also assessed.
Results
Increased EPVS in the BG showed a significant association with lower cerebral tau deposition, even after controlling for other small vessel disease markers. Further exploratory analyses showed that this association was significant in cognitively impaired, Aβ-positive, or APOE4-positive individuals, but not significant in the cognitively normal, Aβ-negative, or APOE4-negative participants. In contrast to EPVS in the BG, EPVS in the CSO did not have any relationship with cerebral tau deposition. In addition, none of the two types of EPVS were associated with cerebral Aβ deposition.
Conclusion
Brain tau deposition appears to be reduced with increased EPVS in the BG, especially in individuals with cognitive impairment, pathological amyloid burden, or genetic Alzheimer’s disease risk.
Potential future changes of climatic drivers for the European Spruce bark beetle outbreaks in Northern Baltic Sea area under CMIP5 projections
Authors: Tikkanen Olli-Pekka , Lehtonen Ilari 
Published: August 2022

Abstract
Recently, spruce bark beetle (SBB) damage has been on an extreme record-breaking level in East Central Sweden. It is considered a result of the increase in temperatures and severe droughts propagated by climate change. At the same time, SBB outbreaks have been less severe in the eastern side of the Baltic Sea, in Estonia and Finland, than in Sweden. This study investigated to what extent precipitation, temperature sum, and droughts (hydrothermal index) have varied in land areas surrounding the Baltic Sea. We studied recent meteorological observations (from 1950 to 1999) and modelled the effect of climate change on precipitation and temperature, using three representative pathway scenarios for greenhouse gas emissions (RCP2.6, RCP4.5, RCP8.5) and multiple (17–23) climate models. Future climate projections (up to 2100) were made for Southeastern Estonia, Southern Finland, and East Central Sweden. Weather data showed that temperature sum has been high and drought severe, particularly in East Central Sweden, in the 2010s, where SBB outbreaks have been a larger problem than on the eastern shores of the Baltic Sea. Future climate projections suggest that an increase in thermal sum will further enhance the reproduction of SBB, especially in RCP4.5 and RCP8.5 scenarios. In all climate change scenarios, drought continues to be a problem in Central Eastern Sweden, potentially facilitating SBB outbreaks. In addition, moderate and severe droughts can become more frequent in Southeastern Estonia and Southern Finland if climate change proceeds as predicted in RCP4.5 and RCP8.5 scenarios.
Maker-Entrepreneurs Navigating a Maker Economy
Authors: Lee Chuike , Vyas Dhaval 
Published: August 2022

Abstract
The DIY and maker movement has enabled makers to venture out into entrepreneurial endeavours. Members of this community are known to experience a sense of fulfillment when personal moral codes of ethics are maintained, even when they are from low socioeconomic status (SES) backgrounds. Our work seeks to explore ways in which this fulfillment is also carried over into an entrepreneurship context. This paper applied a qualitative study involving 9 maker-entrepreneurs from low SES backgrounds, where contextual interviews and a cultural probe inspired method was employed to capture their motivations, business management and overall entrepreneurial trajectory. Our findings indicate maker-entrepreneurs’ clear motivations for being a part of the maker culture, while having a strong sense of responsibility towards the environmental and social issues, as well as the challenges faced by low SES maker-entrepreneurs. This work is intended to add to the low SES maker-entrepreneurship discourse in HCI and identify opportunities to help these entrepreneurs in economic value creation.
Improved collaborative filtering algorithm using intuitionistic fuzzy C -means clustering and incorporating time factors
Authors: Zhang Yanju , Li Rui , Wang Shiqin 
Published: August 2022

Abstract
Collaborative filtering (CF) has been widely used to help users discover items of interest. Most of the existing CF methods collect preference information from other users to predict user’s ratings. However, the user’s interest will change over time, and the traditional collaborative filtering recommendation does not take the change of user’s interest into consideration. In addition, there are also problems of information overload and data sparseness in applications. In order to solve the problem of data sparseness and take the changes of user interests into account , we propose an improved collaborative filtering algorithm using intuitionistic fuzzy C-means clustering and incorporating time factors. Firstly, we introduce intuitionistic fuzzy C-means clustering to complete the classification of items; secondly, the above classification results are combined with the user-item score matrix to obtain the user-type preference matrix; thirdly, the joint similarities are used to obtain the nearest neighbors of the target user; finally, the changes of user interest over time are taken into account when predicting the target user’s rating on unrated items, top-k items are selected as recommendation results. To verify the effectiveness of the algorithm, experiments are conducted on Movie Lens and Booking-Crossing datasets. The Improved collaborative filtering algorithm using intuitionistic fuzzy C-means clustering results show that compared with the traditional recommendation algorithms , the algorithm proposed in this paper can effectively solve data sparseness and improve the quality and accuracy of recommendation.
The health and economic burden of musculoskeletal disorders in Belgium from 2013 to 2018
Authors: Gorasso Vanessa , Heyden Johan Van der , De Pauw Robby , Pelgrims Ingrid , De Clercq Eva , De Ridder Karin , Vandevijvere Stefanie , Vansteelandt Stijn , Vaes Bert , De Smedt Delphine , Devleesschauwer Brecht 
Published: August 2022

Abstract
Introduction
: Low back pain (LBP), neck pain (NKP), osteoarthritis (OST) and rheumatoid arthritis (RHE) are among the most disabling musculoskeletal (MSK) disorders. The current study aims to analyse the health and economic impact of these MSK disorders in Belgium, providing a summary of morbidity and mortality outcomes from 2013 to 2018, as well as direct and indirect costs from 2013 to 2017.
Methods
The health burden of LBP, NKP, OST and RHE in Belgium from 2013 to 2018 was summarized in terms of prevalence and disability-adjusted life years (DALY) using data from the Belgian health interview surveys (BHIS), the INTEGO database (Belgian registration network for general practitioners) and the Global Burden of Diseases (GBD) study 2019. The economic burden included estimation of direct medical costs and indirect costs, measured by cost of work absenteeism. For this purpose, data of the respondents to the BHIS-2013 was linked with the national health insurance data (intermutualistic agency [IMA] database) 2013–2017.
Results
In 2018, 2.5 million Belgians were affected by at least one MSK disorder. OST represented the disorder with the highest number of cases for both men and women, followed by LBP. In the same year, MSK disorders contributed to a total of 180,746 DALY for female and 116,063 DALY for men. LBP appeared to be the largest contributor to the health burden of MSK. Having at least one MSK disorder costed on average 3 billion € in medical expenses and 2 billion € in indirect costs per year, with LBP being the most costly.
Conclusion
MSK disorders represent a major health and economic burden in Belgium. As their burden will probably continue to increase in the future, acting on the risk factors associated to these disorders is crucial to mitigate both the health and economic burden.
Trustable Decision Tree Model using Else-Tree Classifier
Authors: Tran Truong , Pusey Marc , Aygun Ramazan 
Published: August 2022

Abstract

With advances in machine learning and artificial intelligence, learning models have been used in many decision-making and classification applications. The nature of critical applications, which require a high level of trust in the prediction results, has motivated researchers to study classification algorithms that would minimize misclassification errors. In our study, we have developed the {\em trustable machine learning methodology} that allows the classification model to learn its limitations by rejecting the decision on cases likely yield to misclassificationsand hence produce highly confident outputs. This paper presents our trustable decision tree model through the development of the {\em Else-Tree} classifier algorithm. In contrast to the traditional decision tree models, which use a measurement of impurity to build the tree and decide class labels based on the majority of data samples at the leaf nodes, Else-Tree analyzes homogeneous regions of training data with similar attribute values and the same class label. After identifying the longest or most populated contiguous range per class, a decision node is created for that class, and the rest of the ranges are fed into theelsebranch to continue building the tree model. The Else-Tree model does not necessarily assign a class for conflicting or doubtful samples. Instead, it has an else-leaf node, led by the last else branch, to determine rejected or undecided data. The Else-Tree classifier has been evaluated and compared with other models through multiple datasets. The results show that Else-Tree can minimize the rate of misclassification.
Machine learning and conventional method for reference evapotranspiration estimation using limited climatic data scenarios
Authors: Santos Pietros André Balbino dos , Schwerz Felipe , Carvalho Luiz Gonsaga , Baptista Victor Buono Silva 
Published: August 2022

Abstract
Reference evapotranspiration (ET0) is one important agrometeorological parameter for hydrological studies and agricultural water management. The ET0 calculated by the Penman-Monteith - FAO method requires several input data. However, in the Minas Gerais region, the meteorological data are limited. The aim of this study was to evaluate the performance of Artificial Neural Network (ANN), Random Forest (RF), Support Vector Machine (SVM) and Multiple Linear Regression (MLR) to estimate the monthly mean ET0 with different input data combinations and scenarios. Three scenarios were evaluated: at the state level, where all climatological stations were used (Scenario I - SI) ; and at regional level, where the Minas Gerais state was divided according to the climatic classification of Thornthwaite (Scenario II - SII) and by Köppen (Scenario III - SIII). ANN and RF performed better in ET0 estimating among the models evaluated in the SI, SII and SIII scenarios with the following data combination: i) latitude, longitude, altitude, month, mean, maximum and minimum temperature, and relative humidity; and ii) latitude, longitude, altitude, month, mean temperature, and relative humidity. Also, the SVM and MLR models are recommended for all scenarios in situations with limited climatic data, where only air temperature and relative humidity data are available. Although dividing into scenarios results in less input data for models training, SII and SIII showed a slightly better result in the southern areas of the Minas Gerais state.